{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:12:20.432787Z",
     "end_time": "2023-07-06T10:12:20.712677Z"
    }
   },
   "outputs": [],
   "source": [
    "import gym\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import rl_utils\n",
    "from torch import nn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "outputs": [],
   "source": [
    "class PolicyNet(torch.nn.Module):\n",
    "    \"\"\"\n",
    "    策略网络\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim):\n",
    "        super().__init__()\n",
    "        self.fc1 = torch.nn.Linear(state_dim, hidden_dim)\n",
    "        self.fc2 = torch.nn.Linear(hidden_dim, action_dim)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.fc1(x))\n",
    "        return F.softmax(self.fc2(x), dim=1)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:12:20.460730Z",
     "end_time": "2023-07-06T10:12:20.714672Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "outputs": [],
   "source": [
    "class ValueNet(torch.nn.Module):\n",
    "    \"\"\"\n",
    "    价值网络\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, state_dim, hidden_dim):\n",
    "        super().__init__()\n",
    "        self.fc1 = nn.Linear(state_dim, hidden_dim)\n",
    "        self.fc2 = nn.Linear(hidden_dim, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.fc1(x))\n",
    "        return self.fc2(x)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:12:20.477286Z",
     "end_time": "2023-07-06T10:12:20.730629Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "outputs": [],
   "source": [
    "class ActorCritic:\n",
    "    def __init__(self, state_dim, hidden_dim, action_dim, actor_lr, critic_lr, gamma, device):\n",
    "        self.actor = PolicyNet(state_dim, hidden_dim, action_dim).to(device)\n",
    "        self.critic = ValueNet(state_dim, hidden_dim).to(device)\n",
    "        # 策略网络优化器\n",
    "        self.actor_optimizer = torch.optim.Adam(self.actor.parameters(), lr=actor_lr)\n",
    "        self.critic_optimizer = torch.optim.Adam(self.critic.parameters(), lr=critic_lr)\n",
    "        self.gamma = gamma\n",
    "        self.device = device\n",
    "\n",
    "    def take_action(self, state):\n",
    "        \"\"\"\n",
    "        选择动作\n",
    "        :param state:\n",
    "        :return:\n",
    "        \"\"\"\n",
    "        state = torch.tensor([state], dtype=torch.float).to(self.device)\n",
    "        probs = self.actor(state)\n",
    "        action_dist = torch.distributions.Categorical(probs)\n",
    "        # 抽取一个action\n",
    "        action = action_dist.sample()\n",
    "        return action.item()\n",
    "\n",
    "    def update(self, transition_dict):\n",
    "        \"\"\"\n",
    "        核心代码\n",
    "        :param transition_dict:\n",
    "        :return:\n",
    "        \"\"\"\n",
    "        states = torch.tensor(transition_dict['states'],\n",
    "                              dtype=torch.float).to(self.device)\n",
    "        actions = torch.tensor(transition_dict['actions']).view(-1, 1).to(\n",
    "            self.device)\n",
    "        rewards = torch.tensor(transition_dict['rewards'],\n",
    "                               dtype=torch.float).view(-1, 1).to(self.device)\n",
    "        next_states = torch.tensor(transition_dict['next_states'],\n",
    "                                   dtype=torch.float).to(self.device)\n",
    "        dones = torch.tensor(transition_dict['dones'],\n",
    "                             dtype=torch.float).view(-1, 1).to(self.device)\n",
    "        # 时序差分目标\n",
    "        td_target = rewards + self.gamma * self.critic(next_states) * (1 - dones)\n",
    "        td_delta = td_target - self.critic(states)  # 时序差分误差\n",
    "        log_probs = torch.log(self.actor(states).gather(1, actions))\n",
    "\n",
    "        actor_loss = torch.mean(-log_probs * td_delta.detach())\n",
    "        # 均方误差损失函数\n",
    "        critic_loss = torch.mean(F.mse_loss(self.critic(states), td_target.detach()))\n",
    "        self.actor_optimizer.zero_grad()\n",
    "        self.critic_optimizer.zero_grad()\n",
    "        actor_loss.backward()  # 更新策略网络的梯度\n",
    "        critic_loss.backward()  #更新价值网络的梯度\n",
    "        self.actor_optimizer.step()  # 更新策略网络的参数\n",
    "        self.critic_optimizer.step()  # 更新价值网络的参数"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:12:20.512703Z",
     "end_time": "2023-07-06T10:12:20.737610Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "E:\\PCL\\PyCharm 2023.1\\jbr\\bin\\D\\code\\env\\lib\\site-packages\\gym\\envs\\registration.py:593: UserWarning: \u001B[33mWARN: The environment CartPole-v0 is out of date. You should consider upgrading to version `v1`.\u001B[0m\n",
      "  logger.warn(\n",
      "E:\\PCL\\PyCharm 2023.1\\jbr\\bin\\D\\code\\env\\lib\\site-packages\\gym\\core.py:317: DeprecationWarning: \u001B[33mWARN: Initializing wrapper in old step API which returns one bool instead of two. It is recommended to set `new_step_api=True` to use new step API. This will be the default behaviour in future.\u001B[0m\n",
      "  deprecation(\n",
      "E:\\PCL\\PyCharm 2023.1\\jbr\\bin\\D\\code\\env\\lib\\site-packages\\gym\\wrappers\\step_api_compatibility.py:39: DeprecationWarning: \u001B[33mWARN: Initializing environment in old step API which returns one bool instead of two. It is recommended to set `new_step_api=True` to use new step API. This will be the default behaviour in future.\u001B[0m\n",
      "  deprecation(\n",
      "E:\\PCL\\PyCharm 2023.1\\jbr\\bin\\D\\code\\env\\lib\\site-packages\\gym\\core.py:256: DeprecationWarning: \u001B[33mWARN: Function `env.seed(seed)` is marked as deprecated and will be removed in the future. Please use `env.reset(seed=seed)` instead.\u001B[0m\n",
      "  deprecation(\n",
      "Iteration 0: 100%|██████████| 100/100 [00:03<00:00, 25.49it/s, episode=100, return=19.000]\n",
      "Iteration 1: 100%|██████████| 100/100 [00:08<00:00, 11.97it/s, episode=200, return=50.700]\n",
      "Iteration 2: 100%|██████████| 100/100 [00:15<00:00,  6.53it/s, episode=300, return=117.000]\n",
      "Iteration 3: 100%|██████████| 100/100 [00:23<00:00,  4.17it/s, episode=400, return=176.200]\n",
      "Iteration 4: 100%|██████████| 100/100 [00:33<00:00,  2.99it/s, episode=500, return=188.700]\n",
      "Iteration 5: 100%|██████████| 100/100 [00:35<00:00,  2.83it/s, episode=600, return=191.100]\n",
      "Iteration 6: 100%|██████████| 100/100 [00:35<00:00,  2.82it/s, episode=700, return=175.500]\n",
      "Iteration 7: 100%|██████████| 100/100 [00:34<00:00,  2.92it/s, episode=800, return=192.000]\n",
      "Iteration 8: 100%|██████████| 100/100 [00:30<00:00,  3.27it/s, episode=900, return=200.000]\n",
      "Iteration 9: 100%|██████████| 100/100 [00:35<00:00,  2.79it/s, episode=1000, return=200.000]\n"
     ]
    }
   ],
   "source": [
    "actor_lr = 1e-3\n",
    "critic_lr = 1e-2\n",
    "num_episodes = 1000\n",
    "hidden_dim = 128\n",
    "gamma = 0.98\n",
    "device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')\n",
    "env_name = \"CartPole-v0\"\n",
    "env = gym.make(env_name)\n",
    "env.seed(0)\n",
    "torch.manual_seed(0)\n",
    "state_dim = env.observation_space.shape[0]\n",
    "action_dim = env.action_space.n\n",
    "agent = ActorCritic(state_dim, hidden_dim, action_dim, actor_lr, critic_lr, gamma, device)\n",
    "return_list = rl_utils.train_on_policy_agent(env, agent, num_episodes)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:12:20.561577Z",
     "end_time": "2023-07-06T10:16:37.202103Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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q69GmTRssWbIEkydPRrt27RAbG4tBgwZ53Pfdd99Fly5d0Lp1a4wfPx7Z2dk4duwYli9fLrlUxvjx4/H+++9j9OjR2L59O+rUqYMvv/wSGzZswKxZsxQnX4upVq0ali5digEDBqBly5aCGZR37NiBzz77DJ06dQJQOTVAtWrVMGrUKDzxxBPgOA7/+c9/vAZurtq0aYO5c+fi9ddfx0033YS0tDS3VjwxqampmDJlCqZNm4Z+/frh9ttvx4EDBzBnzhy0a9dO0CLjqnv37nj44YeRm5uLXbt2oU+fPrBYLDh06BC++OILvPPOO16H4FssFgwZMgSLFy/G1atX8c9//tNtn2HDhqFjx44YM2YMfv/9d+cMyna7HdOmTZP1OQlRzY8jwQgJaoMGDWKRkZHOGXA9GT16NLNYLOzChQuMMcYuXrzIJk6cyGrUqMGsViurWbMmGzVqlHM7Y5XDoxs3bswiIiLchmwvWbKEtWrVitlsNpaUlCQ5qaCUVatWsTvuuIOlpaWxiIgIlpqaygYNGsS++eYb5z5ik9nxt/GHnhcVFbF7772XJSYmyppUcN++fezOO+9kiYmJLDIykjVs2JC9/PLLkvVmrHJSwTFjxrCUlBRmtVpZs2bN3MrmTyroCgB75ZVXvJ6HMcZOnz7NJk2axBo0aMAiIyNZdHQ0a9OmDXvjjTdYQUGBc78NGzawjh07sqioKJaZmcmee+459uOPP7pdo6pJBT3Jy8tjAwcOZHFxcbImFfTkvffeYzk5OcxisbD09HT26KOPyppUkDHGPvjgA9amTRsWFRXF4uLiWLNmzdhzzz3HTp8+7fW8jDG2cuVKBoBxHMdOnjzpcZ9Lly6xBx98kCUnJ7Po6GjWvXt3tnXrVlnlE6IFrY1FCCGEkJBGOTuEEEIICWkU7BBCCCEkpFGwQwghhJCQRsEOIYQQQkIaBTuEEEIICWkU7BBCCCEkpNGkgqhcG+b06dOIi4vTNGU7IYQQQnyHMYYrV64gMzPTbT1APgp2AJw+fRpZWVn+rgYhhBBCVDh58iRq1qwpup2CHcA5xfzJkycRHx/v59oQQgghRI7CwkJkZWV5XSqGgh3cWG04Pj6egh1CCCEkyHhLQaEEZUIIIYSENAp2CCGEEBLSKNghhBBCSEijYIcQQgghIY2CHUIIIYSENAp2CCGEEBLSKNghhBBCSEijYIcQQgghIY2CHUIIIYSENAp2CCGEEBLS/Brs5Obmol27doiLi0NaWhoGDx6MAwcOCPYpKSnBhAkTkJycjNjYWAwdOhRnz54V7HPixAkMHDgQ0dHRSEtLw7PPPouKigpffhRCCCGEBCi/Bjvr1q3DhAkTsGnTJqxcuRLl5eXo06cPrl696txn0qRJ+O677/DFF19g3bp1OH36NIYMGeLcbrfbMXDgQJSVleHXX3/Fxx9/jAULFmDq1Kn++EiEEEIICTAcY4z5uxJVzp8/j7S0NKxbtw7dunVDQUEBUlNTsWjRIgwbNgwA8Mcff6BRo0bYuHEjOnbsiB9++AG33XYbTp8+jfT0dADAvHnz8Pzzz+P8+fOwWq1ez1tYWIiEhAQUFBTQQqDEUCXldljNJphMHCrsDtgZgy3CLNinuMyOKKvZ7djzV0qREmtFSbkDUVaz6H6uGGMoLrfjWpkdsbYIRFrMYIyhtMKBSEvl8ecKS+BgQEKUxXlcYUk5ACA9PhKlFXacv1KK+CgLrGYTisvsuFpWgcRoK/KvlQEAoixmMADRVjMqHAxmjgPj1aGwpALJMZW/jxUOBsYYLGYTTByHcrsDURYzisoqUFhcjmhrBCrsDpTZHUiKqfzM18oqW2sTo62IjDAhr7AEcTYLisvtMHFAXKQFHAeUVjhQWmGHzWyG2cyhvMKBxGgLzhSUXD8fEGEywRphwuVrZYiPsjg/Q1X5peV2xNgiUGZ3ID7SIvi+VF07s4nD2cISxEVacK2sAnYHQ5TFjGhrBApLylFudwjKZIwhwmRCcbkdHIAyuwMxtsrPGWE2CepQ9X0pKbcjIcqCwpIKVN2qE6IsKCguF5R9paQciVHCe92V0nLYzGZUOBxIjrWBMYYzBSVw8G75ZhOHaGsEzCZOcH4+1/PxVX3/TRyH2MgIFF7fL9YWgZJyByocDo/HSZXlSYTJhCiLGVdKPddDCYvZBFuECUWlxrb+x0dZnNdDLf7PgVIx1giUX/8d0orjOMRHRoj+HMiVHh8Ji1nfNha5z++AWvW8oKAAAJCUlAQA2L59O8rLy9G7d2/nPjk5OahVq5Yz2Nm4cSOaNWvmDHQAoG/fvnj00Ufx22+/oVWrVm7nKS0tRWlpqfPrwsJCoz4SIU5FpRVoPX0lGmTEYtnjXdF31nqcKyzF1pd6O29q/9l0HC9/vQ9vD2+BO1vVdB4766eDmPXTIaTF2XDuSikiLSaUlDvw8dj26N4gVfK8j3+2E8v2nHF+PXNYc/z4Wx5+2n8OG6fcgq92/IWZPx4QPX5c12x8vzcPf+UXa7wClQ9BsYdMpMUEhwNeb85RFjNibGZcKPL8YPQkIz4SeYUliuoKAFazCUsn3IzdJwvwwtK9eOvuFvhu92msOXAe8ZERKCwJju7yt+5ugS1HL2Hx1pP+rgoJY6uf7o66qbF+OXfABDsOhwNPPfUUOnfujKZNmwIA8vLyYLVakZiYKNg3PT0deXl5zn34gU7V9qptnuTm5mLatGk6fwJCpG05ehFldgf2/VUZXB85X9lde/DsFTSvmQgAePnrfQCASUt2C4KdD38+CgA4d6UySC8prwwIXvp6L35+7hbJ8/IDHQB49ss9ztdfbjuFvX8VSB6/fM8ZnC6QDhTMJg52h/dGYqm/pqs+kxgTBzAAxeV2FCv8S1dOoGONMKGsQliHMrsD+89cwQtL9wIAJn++27nNW6ATYeJgMnFuZUqxRZhQ4WAer6XFzKHcfuN9T/UVs+dUAXadzHeWY+I4OBgTlFd1/iqMCQNP/jagsgXNFccBHICq6keYOJhNnNf68ctyPQ+/niYOmloG7A6GCoc+ZUmR+jxy8X8OzCYOETKuY5Vyu0Px90CMt58DJThOfT20CphgZ8KECdi3bx9++eUXw881ZcoUTJ482fl1YWEhsrKyDD8vIZ5UyAgS7CK9zdEW43+FvbWgNKuRgK71UzBn7RFD6/FApzr4I68Qm/68ZEj5v0/ri57/WouTl4QtWA4Z3x+g8jrwA8d/3d0C7bOT0Cl3tew6HHi9P2avOeyxpW3OyDYY98k2AED7Okn44IE2aDl9paxyy+0OVP0ILRjTHp1vSsGeU/m4/b0Nbud3vs67gr6z1gMAmtaIx7LHuwr2rfO35W7nubleMmomRmPJtsoWpH+PaIX+zap7rR+/LH4dAGDFvjw88ul2AMDA5pn49wj31nq5vtpxyhmwDmtTE28Oa6G6LClNX/kRRaUVGNAsA3NGtlFVxv/7+U+8vnw/AOD5fg0xvls92ce+uHQvFm4+AQB4486mGN6ulqo6AMD+M4Xo/87PACp/xr97vIvqsvwpIIKdiRMnYtmyZVi/fj1q1rzx12xGRgbKysqQn58vaN05e/YsMjIynPts2bJFUF7VaK2qfVzZbDbYbDadPwUh0v67/S+P78t9mHoSKSNnxxtvZ/fWrWQycfDFH2wcV9mFZRSziQMH9w8iJxgFKq+D4GuusgVFLzG877XJBEV/rdsdDOz6d7rqKH5+lif8qnu6LmL418H1mqghrEdw+PzhTvjPpmN4tm+O6jKsvBYUq0EtUOHEr1eQMYaJEydi6dKlWL16NbKzswXb27RpA4vFglWrVjnfO3DgAE6cOIFOnToBADp16oS9e/fi3Llzzn1WrlyJ+Ph4NG7c2DcfhBAvCkvKsXzvGY/b5DxMxW7y0QY+/GVjTNeHOh+/6Z4D58xtMgLHeQ7axFrVXLl2M1R16ejFNRldSRdMZUJ4VcUq/6tKvK7So6Ew94tfd7nfXg7C7hYlXS9i+D9bWotTG8Ap1TgzHrlDmiMpxvsAGTH87iJbIPyeBzm/tuxMmDABixYtwjfffIO4uDhnjk1CQgKioqKQkJCABx98EJMnT0ZSUhLi4+Px+OOPo1OnTujYsSMAoE+fPmjcuDHuv/9+vPnmm8jLy8NLL72ECRMmUOsNCRglZeI5JhV29S07ckZjSeE4QI/xmEY9NpJirM48JY6DocGOGLvM0SyuLS0mjlOVoyB2SITJ5PK1/LIr7A7ciHUqj4uLvHH7r5sag1nDW4rWQ8mn4F8HLbkins6tNeeDH+D4MX1EFi0tO3oGdYKyAvyaSfFrsDN37lwAQI8ePQTvz58/H6NHjwYAvP322zCZTBg6dChKS0vRt29fzJkzx7mv2WzGsmXL8Oijj6JTp06IiYnBqFGjMH36dF99DEIU48/4oGR4risju3Vk4zjD7oKCYAfGBzueAj+5sajF7NKyA3WXRezh5FqWkkCiaqg/v5wI3gN0aOuaSIwWtkLwAwu5QQbHwaVlR3vngZ7dWMH04Laab/ysWzUkBZNKfg125EzxExkZidmzZ2P27Nmi+9SuXRvff/+9nlUjxFD8H32HjN8DsYeN1pad67XRXIIOf8B7lBx74wFc2bLj+5u+XWYwanZ5sHM65+y4UtLKUWFncOnFEvA0wkZNNxYAmHlBny4tO4KKaC7OqMJ0J+jGUhjsCAJmrV1//NYwbUX5FYWLhPgBP7zQ1I3lpaVjz6l81WXLxphh+Q+xtht/j5k4Y3N2xMidk81Tzo6aZ71YYMF/X2nXY4WDOX/o+EHShJ710DA9DsPbuY9GFbTsKDiXoGXHrEeww8/ZCebHrTKCbixq2dEsIEZjERJu+K2acuanEU1QlmjZOX7xqtvQYs918bqLV0a17PC7WmDwaCwx8lt2POTsqAgCxY7QElDaHbycHV4xz/bNER0xpCZXhuM4QQuX7jk7WssSdM1pLMxgWoIdo7r+Av6iSaBwkRBfkLhHyBmNJbaHVEvH76d9NDO4yCgmPfATMytHYxl7y/L0OWb9dEjWsR5zdlRUV07LjlKCnB0V9ZB9DAAz70A9RmPpGaAY1iNmAGE3VgDk5gU5CnYI8QN+8CKnZUeMHs3bVWfvWDdJZQHMsJlR+QGEv0ZjyZ1nxzVnx2TS94HKcXAOZb4lJ03RsYKcHZmVMqnsPorQOWeHX4TWbqygSlDWlLPDe615BJvn18GGurEI8QN+15GWeXYkj1F4kJYHiZ4PDv4yCBZBy45/gh253HJ2oC5BWXQ0Fjh8/0RXbPrzIgY29z4rMd/GPy8KSlJRKXm7ccIAR5fRWDoOFxcm2wb2o9tGOTu6oitIiB8w8HN2tK9KrLoe7Eb+kKZgR8cHB7/rShDscNrW5TGax0kFdUxQBoCMhEgMblVD05pOsicIVJn3ESGYZ0fBgTLqobVtIZhadvhdV4pbdlQml3suy/PrYBO4dw5CQhi/ZUfuaB/llN2Z1N7Ioqxm3Vt2PL3moG6SPiW0JGu7jjzSe+i5XkXJz9lR3qLCwXVSQX3n2TEqET4Q0WgsfdEVJMQHpFo+ZE0qKHK4nLmqvKkqQemDuWPdJNRJjsbrg5vp+hAStuzw80YCO2fAfTSWvn8J61WU7JFVgtfyR2PpvVyEvt1Ynl8HogidZqLW/jOoXyuRP1HODiF+pmWeHT0pvZ+OaF8Ld7SsAQBY88c5L3vLx/8rVtBdY/AkfVq55qdwUDn0XOQz+rplR5CgrODPYt2Hngu60/TsxgrcnyXAJUHZHLi5asGCgh1C/EDYjaU+QVmPOXKYh8nm5OA/yIzqxnJNUA7kbgxPLTuqJhVUsUVR+apyduS3BvHj00BbCDSY2ibiIi14aWAj2B0MCdHSK9QbKZgCRCkU7BDiB4IEZRkRi9geUkcqH42lbH/BiuQ63gT5AY7VJUHZ6JutluLdHuwq62vEPDuCchQELkrPXTlrtD7dL57OrXkYdZAl2z7Uta6q44Ltc/oC5ewQ4mcVBmUoK73HKW/ZEba66IUfNAjm2YFxkxfqwdMMynq2ROmXs2PsCfk/R/oMPdePmjwkEhoo2CHEB1wfMHrNs6NLN9b1/7W07Oj5UOeXZYkQtuwEds6Oy2gsqGzZEXvfx59dmBisLkIy09pYfqHnfELBlNQthYIdQvxArxmU9aT0QWKW6MZqVD1edT34Zfk6Z0fb0HPXGZTVVVY0QVlVaZ7Kl7cfv/pqz63PchGeX6sry5g8MxL4KNghxA8ULwQqcmdmklk7yuqiNNiJkEhQTo2zqa4P//nIz9kxmQJ7NJZrN5bamgZMzo4O+UYBtxCojmUFMgoQ3VGwQ4gf6NWyo0c3VhXFCc0GJSgLJ6VzT/oNVO4zKAdmZZVMEKjlGEC4KKhawiHw4ZWgTPRDwQ4hflZ+fZ6dVfvP6lqunIftv1YexMlL1wBobNlRVjVJYpPIBXzOjks3ltqqiubs+HHoudqgWmtw4loPzS07Oo7sCmSU1O2Ogh1C/EA4z07laKwHP94mur/YfVly6LnMuhy7WBXsyDzgOrMgQVm/m2Ct5Gjna9dES6NydtrWrqa5DNeWHdXXRMGkgvVSY5QX78NuLD0I6qu1SyZEZgMmytE8O4T4gNtfxryvvT1Unv9yD/KvlcssWD3lLTvCkVJ6yaoWjU/Gtke1aCtOXb4mOIfWoOqFATnYfaoAy/eccb739vAW6NkwzXkOtXTL2VGw75KHO+HnQ+cxaclu+eWraNmRXbYBIYRwbSwKUeQwam6iYI4QqWWHED+Qm1h8trAES7adNLg2lTTNoKxjPUwc0K1BKprVTHDrwtB6nla1quHmesmC9+5sVROJ0VaNJctv2RnZoZaq8j0VlxJrw52taiorR+f9jKZnN1bYZCgTNxTsEOIHchtkyiqkJxzUc9C64nl2BIt06vfkEOZ5CPN3NP+V6mW7nkPPXataOzkaW1/sjaykaEgRH42l7rPXT4uVVb7U+YxsDfJapmELgYZutCP43mktK0S6/ijYIcQHXFty5D5T9Rxt5Y2WeXb0vAuKjZjRe0ZivbmPxhJut5pNSI2zeb1UYg9htR89Kca11Upmzg7vtdyfQ0OCHcGPmdYuGf0CJxJcKNghxA8cMp8e3tbNktqsfCi5sv3NOv71KFauawCmx+geo7jn7Hiuq7egUu95diLM0kGYGLWtdcmx2rsExeqh9dtPvVjKhcpwfUpQJsQXXIISuX8pewuKpHJ/lN6YlHaTmCSCEi1MIkEUx2nveDDyZu2WsyMSPKofkq7uQLNLRWTn7KhMUO7RIBXju9VFYw2zaIvWI8wWAlVLx0sWMijYIcQP+DMoM4mARmqb3pTeE416cIiVyyGw50aR27Lj7TOIbVXdsuPjyQ45jsMLAxrpV57Ia+J7wZznRN1YhBhg+/FLGDr3V+w5lQ/APUdHbgjjbXJlPWMhpa0zRg0JFrTsuAQ+AdyL5dZdJFZXrzk7On9GTwuUyqEqmDUkZ0e/FkQ9F8gMaDrmOYUKCnYIMcDQuRux/fhljPhgk8ft/CBFKl6Rm9ujB6WBhFhQomc9XEeCaA+q1OXLyOHWXaQy90bvBGW1OTv8eshOUJZbKQX0XedJv7JIcKFghxADXS2zA3B/WDgE3VjixzukR57rOvRcafeGUQ8L4Zpb/PNxhj+gtMSWFpndRepnVhbfNGdka9Ft7jk78s4fKK1oenZjhUuXmK7D9UMkQKRghxA/YILXnp+weQUl3hOUpUZjKbydK30IG5WgLBweLByJo7kbw8CbtdwZlL3WQbT7S/xAi1n8Vu4ehHk5v3M/5RfLiHwgPRcCpczd8EXBDiF+4HB4b9npmLvKx/PsKNvfqOeG6JB2H7TsaOGes6OuO0pNkCRVplsQJrsbSzmju7GIPHrOOh0qcxNRsEOID8hdHsKV13l2pMpVmoOjMNoRztKqZ4Iy/xy81wjstZHk5+x4yxvSO2fHtV7ySgqU7gt9Z1AWCaRJyKNghxA/CMQEZeXz8tx4rWd+h1j3WOVyEdrKNvIBJ3dtLNUpOxIHSpWpfjSWigRlQ0Zj3XitZzdmAMfNmunZ6irMcwrei+bXYGf9+vUYNGgQMjMzwXEcvv76a8H2yoRE938zZ8507lOnTh237TNmzPDxJyFEmtoEZa/z7Phx6LlRo7HEmuA5cAHdsiO3bt4eGKLdWFLHSGxU240VKHTtkhG8DrILQTTxa7Bz9epVtGjRArNnz/a4/cyZM4J/H330ETiOw9ChQwX7TZ8+XbDf448/7ovqE6Ka3JWyvM6zI7FN6a1cW86Ont1Ynp9ugT7PjuuMyWLdgt4+g9oh62LkTnaoB2NydvQcWRQa+SfeCD8btYYBfp5BuX///ujfv7/o9oyMDMHX33zzDXr27Im6desK3o+Li3Pbl5BA4japoMyWHbu3aEdHWiYV1PMeyA8aXHMsNK967jVfRkPZcA0q1J1DNNiRuMpS23zZsmPMaCz+ax0f3JpKIsEmaHJ2zp49i+XLl+PBBx902zZjxgwkJyejVatWmDlzJioqKvxQQ0LkEww9l5xnx9vQc/2CIU8PKqlWCLEh4lqJdY+ZOOM7HrRcTtdLID4ay4jEFvFNrvVQNcoqQBKUie+FyvUPmrWxPv74Y8TFxWHIkCGC95944gm0bt0aSUlJ+PXXXzFlyhScOXMGb731lmhZpaWlKC0tdX5dWFhoWL0JAdyDErlBirZVz5Xm4IiUIXISXycog9NjuQDf0XsGZbWVd5uCR0U5gTODsn7f/2DukvFGzxFsoSJogp2PPvoII0eORGRkpOD9yZMnO183b94cVqsVDz/8MHJzc2Gz2TyWlZubi2nTphlaX0KkOASjscSfJN66sTYfvYT3Vh/CYz1ucssRUdrq4ymQMHGAXcb+et5QRdfGgvZgx5fUDz1X9j7gZZ4dt5YdI/uxDChSx6Baz8ApXITKNQuKbqyff/4ZBw4cwEMPPeR13w4dOqCiogLHjh0T3WfKlCkoKChw/jt58qSOtSXEO8HQc6luLC8By96/CvDP/x3EN7v/cj+HwjqJtuyIMGpki8klwOHXJZjutXqvcSU9Gkt8a9MaCS77qqyAn+g7N06QfXiVKDfJXVC07Hz44Ydo06YNWrRo4XXfXbt2wWQyIS0tTXQfm80m2upDiBFcYxZ+a45UUFJhlxeyHL94zcNJZR3qpDRnx7ih5+ItO9pH42g7Xgmxa+c6aksuNX9Vvzm0OdrVSRKWo+70shjRaqRrN1aIjCzyJU7kdbDxa7BTVFSEw4cPO78+evQodu3ahaSkJNSqVQtAZT7NF198gX/9619ux2/cuBGbN29Gz549ERcXh40bN2LSpEm47777UK1aNZ99DkKU0qtlR/IcCqMdTzd/qW4jo5q3hUGCMPDRoxurR8Mbfwi1rpWouTwx4jMhe+vGUt4iJLatT5N0t+5NdWteKT5EN3oG1Ua1RgYa1xZR4udgZ9u2bejZs6fz66r8m1GjRmHBggUAgMWLF4MxhhEjRrgdb7PZsHjxYrz66qsoLS1FdnY2Jk2aJMjjISQQyQ1i7F5WPdeT55wdecGOayuGlturMEFZeD49gp0aiVHY9lJvFJfZUT0h0vsBKom17HhPUFZ3nOdjOA85O8r5dQZl/YskSoRIa5hfg50ePXp4TaIcP348xo8f73Fb69atsWnTJiOqRoihNv15yfmagYn+HngbjSVF6aEec3Yk9hfmUrgkRys7tbAe/Hl2XEZmaf/LvrKAlFjju7FFc3bUJihLzbMjEVj5dJ4dI8r0QRdpyOF/Tj9WI5AERYIyIcHONfB4bdnvvI3ix3mbZ0fJOb3x1Goi9UAQW7BTK5PEjTqQH1DRVrPga07k7qo6QVlyNJZ415f7PDsBfBE94NdX67RSoZJ/QpSjYIcQP2MQv4lrmUFZ6ZGeWhxcWwXE9nc9VK9uLNe8ID1n0NVbzWrRqJcac+NcKuugZzDCcZz799DIlh0jurF0fEqFS4KyMGdHa1mh0UpEwQ4hPiCVLMyY+FZt3VhK59lxf0+qy0U4RFzHbiyRSQU9tVIEmgk9b3K+Fqurt8+gLjfH8/smzkM+lY7lu+1nxGgsFfUQL0u865WENgp2CAkAYoGJpm4shfuLTSooxqj8B6nE3mB6PInn3ng5TqQMNZMKcuDcAlYjE5SNwK+/5m6scGnZ0fFz0qSChBBdMIgHJhU+zdlxf0/uzU2P9Zc8HSycZ0d7N5Y3k29toFtZomtjqfwIaloiPJ3LyAeWEUUH8kr3JHhQsEOID0gFHkbNs6OU0kkFhccKv9arG4v/gDdx+uZveDK4VQ3MHdna0HMoGY0le44ZBQGBkbGDMUPPw2QEVYAKlaRuCnYI8TOjEpSVhhxK59nh0/MmKJ6g7JucneqJUbqUI77quTeeE0KlYx3p/KBg7r7h11ffbqwguxAKUG6SOwp2CPEBqXt0ZYKyyDw7fu7Gkh3s6NiNJdayocdtW87H0evRoLq7SqwbT8PMx2KtZfozIEFZxyJDZWSRL4VKUEjBDiEBQCww0bZchDJK59mR2k/s3FP653gvS6RcX7Xs6HUOvesq2bLjJRnaqDmRfEHPbqxgbuFSwuVvBAIKdgjxCalh4FJBiZblIhTHSRpaduTu93D3et6rITKpIAeZLTOSo5ZkdCLp9HBQW4xYW5aq0VjObizfPPEMydnRs2VHkPBO5AiV6xQUq54TEtICZCFQpUPP+Vx306sbS82kghy0JUgrfbjOu6816qfHaS7nxnGen8hqApaq75+vWnaMKDrQ51YKRNSw446CHUJ8QDJnB0y0FabC7rvRWFqGnhs2GsullUdeyw6nKZOV35oSZTGjuNwuuX+/ptXF66Hq/CqOER3mXvm+73J29KdnbYUtZcF1HfwlVC4TdWMR4meMibfC+HYhUPU5O3r+9S32V6nJJO88anJb+PgLkXapnwKLOfjv9mZBAGnceYKqGyv4v62iwmXUmRIU7BAik93BsOHwBRSWlOtaLmMSgYkPE5Q93RPVBjFabq/iLTucrG41fZcUADISIrUVqPT8KvJKvH1mX+WqGLJchA8CaSIu2FoCxVCwQ4hMn2w8hpH/bzPumrtR8bHeYhbRWEfxmfjn9GHOji+SSDl5Dz6tN2d/jACTOr+sY7xsN5k8B5DhRjhKKXSvg1iSfzijYIcQmb7edRoAcODsFV3LVZpIbBQtkwoaFRDo3SIhqxtLcE7f/11rxIRwrguqGiWE4wcS5CjYIcQnpFY9F2+F0TJjrC/XxtLzISe66rnP6iLMb/FnS4jaeY5cBfM8O/oKvxYPzd/vELlQFOwQ4mdSC4G+t+awz+qhZW0sXROURYrSI39FTkuJa2Dg83u9qtYs6T05FUGjGoH+XAyXBGXijoIdQnzA20Kgmtf88fCYUT7Pjqf3ZLamKDqTt3p4Hjnkq4eTa1K0r5/gwrQSvbqxdCnGq8DokBUnTFCmaEeOUAkKKdghJAR4Cmz0GHru9wRlkS4tyeM1PsRMwieiHxKUlXe1eKuiOVSeWBpxIoF0qBHmuoXwB1WAgh1CfEA67mCG/EmsONjxdDfwwxNBmCDs+bUUyW4sOUPXXfI6guFR4a2OPlsuwidnUY+GnisXKteJgh1C/ExqUkFN5SrcX0vOjr5EWnN0Gobt9XiXliVfx3uuw+314DGQNUCgd2OFCz0XTw0VFOwQ4mcM2nN2PJaryzw76u6Ueq1N5Y/meNf4ytfdAGouubeWm1BZX0pzbhslKCsWKvMyUbBDiA9IJygbM9OO0jI9JyjrUhWF9fCcs6LHPVdOEXrnddRIjAIA3No4Xdb+rt1o8o6RFirBjlZGzGEUiHw1Y3YwoYVACQkBety4PZXhy8UsPR6r4qatNXAUyxlSa+mEm/Hr4Yvo3yxDh9LUCZVYR/NSIJS0o1ioXCZq2SHEB6Tabiq7sYzox9JehNobnV6rnktNKlgt2gIAiFDQ/KQ4QZnjNOdTpcVFYnCrGrBFmGXtr2YRR/5uNatFuW33VctOMD0Yg6muShmR9xXsKNghRCaj7hlMh8FYHoeeKyzV20KgTTLjUTclRnHdlBJrgnetX3p8JLa91Bvrn+up6/m1tOyYdej345egpjhP30dfDT0P9ARlWg1cuVC5TBTsECKTtkU5pcs1JkFZexlmwQKSQEqcTdZxmrqxRB5InspMibXBFiG8jWn+3C4nUlJev6YZaF4zAWM619Hl/LJbdrzOoKy+OiT40Dw77ihnhxA/q0xQDoCh557eU3mf1DYaS16Cblp8pNv+MkqXsYf6ph1bhBnfTuyi7CAdeHu4UTdWJVoNXLlQCZaoZYcQHzCi5caIc7aulSj42m3pBB98Dm8jsN65pyX6NcnAc30buu3vietn8sZ11XNfUzMayxuaZ6eS3qP7AhXNs+OOgh1CAkEgPCU44N4OtQVvqU1B0XJ/FUtKrrpEd7SsgXn3t0HTGgnX9xEva/odTVAvNVb1+Y2ZFECa1rlgvOVehTOaZyd8UbBDiJ/pkaCsx0KgleUIuS7K6YuHv9IHkutnd62j0vIEgYExK3lIUvMM9javiq+e64EeP4TLPDt6CpWgkIIdQnxAeug5C4gEZc+5HvztvqF4QjSdK8bv8nEwZsy0AD5GI48qhUvLDk0q6M6vwc769esxaNAgZGZmguM4fP3114Lto0ePvr42zY1//fr1E+xz6dIljBw5EvHx8UhMTMSDDz6IoqIiH34KQrTRY20sz0PPlXN9AMif50W/W6rrPDfez62kbO+E3Vi+J/zMykdjebpmegyJJySY+TXYuXr1Klq0aIHZs2eL7tOvXz+cOXPG+e+zzz4TbB85ciR+++03rFy5EsuWLcP69esxfvx4o6tOwpCWx4VU48Duk/k4nV+soXQVJ/XAU9DAedvhuropMehaP0XR+cTwn8tyntGuu/A/NmPKuyv4gYHDD9GOmtYHb3/J+yrWCfQ2sHAM+ahVr5Jfh573798f/fv3l9zHZrMhI8PzNOv79+/HihUrsHXrVrRt2xYA8O9//xsDBgzAP//5T2RmZupeZxK+jLqRXy2zY+jcjbqXq0fLjtzEVo7j8J8HO6DO35YDAGonR6s4+42ynK/lDBXX+WbO/8wOA7qwqsVYJbcrb9fxjh5419GkgoqFymUK+JydtWvXIi0tDQ0bNsSjjz6KixcvOrdt3LgRiYmJzkAHAHr37g2TyYTNmzeLlllaWorCwkLBP0LCnad7mmBSQXhvLFo8viNGtK+FZ64PC9daD3kJyhLbOOWz5gpaQQxIUG5buxoe7VFP1zK99Xz5qmUn0J+LRgzrD0R6L2YbCgI62OnXrx8++eQTrFq1Cv/4xz+wbt069O/fH3a7HQCQl5eHtLQ0wTERERFISkpCXl6eaLm5ublISEhw/svKyjL0c5DQEMj3DI+jsVQ8pd3KUdil0rFuMnKHNEN8pEX5ya9TOkzadXetwYmwG0v/lh2O4/B8vxz0ykkT2X7jteyWNS8PcV8NPTe6G6tR9XhNx4dLgrKeQmXUWkDPoHzPPfc4Xzdr1gzNmzdHvXr1sHbtWvTq1Ut1uVOmTMHkyZOdXxcWFlLAQ3Rz6OwVf1cBgPLFRT21erg+JH2Sk6Fx6Lnm0xvcjXXjPKJbZOyjTLDPs7NyUjccvXAV7eokaSonuK+CfEZ0hQa7gA52XNWtWxcpKSk4fPgwevXqhYyMDJw7d06wT0VFBS5duiSa5wNU5gHZbPLW+CFEqUc+3e72nl9mUFZxjHvODm+bptrIZxJp2RC7ht6e41qG4frj+6amvt666nwV6xh1mvrpcaifHmdQ6URKkMfJTgHdjeXq1KlTuHjxIqpXrw4A6NSpE/Lz87F9+42Hy+rVq+FwONChQwd/VZOEuYtXy3x+To9Dz3V4ULu17Pjg6a/n+kVaq+tgCPwhRi4sZvfbuq+Gngf6pVKa/B6sqLvOnV9bdoqKinD48GHn10ePHsWuXbuQlJSEpKQkTJs2DUOHDkVGRgaOHDmC5557DjfddBP69u0LAGjUqBH69euHcePGYd68eSgvL8fEiRNxzz330EgsElD8seyA4oVAPQ09d2kx8EWwYxJppRC7abu971ZF9d1ClYu0GkO0pYr/WnbOzg33ts/Cws0n0LtRuvO9YO/G0gtdBeVC5Zr5NdjZtm0bevbs6fy6Ko9m1KhRmDt3Lvbs2YOPP/4Y+fn5yMzMRJ8+ffDaa68JuqAWLlyIiRMnolevXjCZTBg6dCjeffddn38WQgKNHoGJyaWVxaG5RO+UjpiR+gtd6zPeyJwdMWqGRPMPibFFYMVT3QTbaU7BSuES83ESX4UrvwY7PXr0kLwh//jjj17LSEpKwqJFi/SsFiG6M/qZqUeTvD8no+NTvDaWgXX0y6SCRpQZLk95L/i/J/5obQ1GofKzE1Q5O4QEg2C+Nbje2NwWAvXB80Es2VZOtw/gZSFQhd8df7TsqCPdVUfz7JBwR8EOIT7gj0em4oVAPebs+P7xpTQgMbqOvl4IVPtyEd6nEDBKwIeGYRKN6TmpYKhcMgp2CAlRaprpXW9srg9RLQ+z9jLnSFHaCuFtdy03a3/Ms8N5aaVRQ22wUzXx4dgu2fpUxM+0tPKR4BZU8+wQQjzTZ+i5pxYBdfVxtfmFXkj2siaUsxZaZ1CW+NzKR2P5vrVCzQNZOILLfbtJ5Tfygwfa4vyVUmQkRCquRyAK9PrpRcvcUqGKgh1CDLbpz4u4Vlbh8/PqvhCohrtmery8h2XlOZWVbWQ3lpEtO3KKlt+NJb2j2qDVbOJkBzpA4HdjhUqyrS+FyiWjYIcQg93zwSbDz6HLaCyPia36TfAnvx76nSk5xgaOU798hz9GY/HpdSVonp1K/KsQyqOx1MzVFOooZ4eQEHSusAT//PGA4uNcgyZrhMstIghGJzEA793bCmM7Z6N/U/FlY2QX5mNKV2kHvD/c6HlH1AqVYIladggJQY98uh0VCpslPN3SInnBjr/veZmJ8rpTGGO4rXkmbmteOYu6llYvB2M+j+/U1NdbbyO17FQKm8vghxbZQEctO4SoMHTur/j9dKG/qyFqx4l8Vce5PgxsFrPga3+063w3sQs+GdseNatFay5L6cPOwVhIdHfQPDuVhLNzB3ptiZ4o2CFEhe3HL+OBj7b4uxpOejyQPTVXR/KCHX89HJrVTEC3Bql+ObeRYc6Yzp6Hc6ta9dzrpII0zw4QPi073kbnhSMKdghR6UJRqcf3g7mP27XmkZbA6caSy/WBq6XeRiYod6mfgk1Term9L6ivXvPs0OJYJMxRsEMIERUZ4dKNFeh/unuhNBA1evZkT8O6lS6ECsiZQVlpzdQJ9JCKf51CoXtSDE2e6I6CHUJCgF4LgbrGAoJurCC9Z2qdQTnYAjzqxiLEHQU7hMgUrA97LfjdWEBw/DWsZ3DicOhXllxqhp57Q6OxKlGCcviiYIcQmYLtL3ylKp+HwgeAa4Jyr5x0AEBKrM2HNdOP0sebP1Y9V5Oy4y2pmWKdSuFyHYxYXy3Y0Tw7hBBRNpdJBSf0vAnZKTG4uV6yn2qkXLAljKtb9Vz64UatGJXoKoQvCnYIkSmQn5m6DD0H5zVnxxphwuBWNTSfy19UzbPjxxY9vYIUSlCuFGyBr1ph8jEVoW4sQmQK9W4sT/g5O+H4+f2zNpaKGZS9HB/pMjmkUQL9RyRc1sYi7qhlh5AQoNdCoK6l2HhDz8sq/JCt62dGDz33RF03lvQx47rWxf9+z3MuoUFCG00q6I6CHUJkCsebho3XslNaYde17DrJ0Th28ZquZXqjNCj0R2uWET9mCdEW/G9SdwNKFgr0XxGafyZ8UTcWITLsOZWPnSrXmwomrjkNESZeN5ZO5/jykU4Y0T4LUwc11qlEYOaw5qLbtM2gHBxdHWomIjRCoF+tcMzZoaCuEgU7hMhw+3sbZO8bSrcWfmKrXs/9tnWSkDukOapFW/UpEMBdbbN0K4uPwfddWcKRVfJ+moyYm4eQUELBDiEaHLtwFcPm/orVf5z1d1U085Szw/+rUO+ETv5Ed0aOFtIy50iwzLMTKIKtvqGK5tlxR8EOIRo888VubDt+GWMXbPN3VQyn93OfH+zwu8vUerRHPQDASwMbaS6riv9nUJZ5jMhrQkglSlAmRIP84nJ/V0E3nubZgQHdWFX48Y3JBEBj/vNzfRvi/o61kZkYJboPBQIkLKgImEMdBTuEaBDhq9na/MTIGyW/Zcesw4k4jvMY6ARbgrKqLogAebgFeoIyCV/UjUWIBp4WWPTHw0avfBqpuis9Q7VoCwCgbmqMx+2CYCdAg0bGfD/8XM1IGsrRIEQaBTuEaBBhdn+y+GO0sh7n9LymEv8cyk7yxSM34+62NbFgdHuP2/nxjc+CHYWnsft56HmwBS5BVt2QJczhou8KQN1YhGgSKC0SRj2StQxjviktFm8OayGrbCOvo5aSGWNBEXEEyrwqwdSNRctFhBdq2SFEAz1yTQJF5dBz330efoDjqTswEPhlBmVB4CLzGENqQoKVcK4mP1YkgFCwQ4gGgdKyY9RTWdiNpW/Z/EtnZKK3mlaPBzrVBgA816+hz1sAODVjzwNEMNWWunfCCwU7hGjgKWfHPwnK2nFwn1WQ/1kMnVQwUILG66bd3gS//u0WDG9Xy+fnVjNnDqemOYiELJp3yR0FO4RoYNZhMjw9+KK7Re9z8J/Pvmohk7+K+I1h7H4djaViUkFKRSHEnV/v1OvXr8egQYOQmZkJjuPw9ddfO7eVl5fj+eefR7NmzRATE4PMzEw88MADOH36tKCMOnXqgOM4wb8ZM2b4+JOQcOWhYccv9Gh18bZchN70nmdHTDCvFZVVLdrfVVCE4qzAEMQ9oYbx62isq1evokWLFhg7diyGDBki2Hbt2jXs2LEDL7/8Mlq0aIHLly/jySefxO23345t24RT80+fPh3jxo1zfh0XF+eT+hMS6i07wm4sffFbcwIm9ykA8APMibfchNjICAxoWl36GOq3UIxGY4UXvwY7/fv3R//+/T1uS0hIwMqVKwXvvffee2jfvj1OnDiBWrVu9KXHxcUhIyPD0LoS4kkozaDMQboVRO/Vv33VjaU1DvD1I5F/XaIsZvz9zmbejwmQCCcwakGEv8b0XQGCLGenoKAAHMchMTFR8P6MGTOQnJyMVq1aYebMmaioqJAsp7S0FIWFhYJ/JLQxxvDk4p14bdnvupYbKC0Svngg630O4arnxl3HYPv7XRCcBcaPl2zBdK0DJUAkvhE0kwqWlJTg+eefx4gRIxAfH+98/4knnkDr1q2RlJSEX3/9FVOmTMGZM2fw1ltviZaVm5uLadOm+aLaJEAcOHsF3+yqzPd6+bbGupXreRSR72+ies2g7JazIxh7rv0cfMLRWPqWrSc/T6Isj4HfJxJ8aPkQd0ER7JSXl+Puu+8GYwxz584VbJs8ebLzdfPmzWG1WvHwww8jNzcXNpvNY3lTpkwRHFdYWIisrCxjKk8CQkm5w5ByPSco+/5pE4z5B/w40Vd/ZQdFsrIguTQI6ssTXLUl4STgg52qQOf48eNYvXq1oFXHkw4dOqCiogLHjh1Dw4YNPe5js9lEAyESmuwOY4KBgJn5V5ePx7n9FcgPQvS+gjTLq2eCv8rlHkMJyoRICuDG4xuBzqFDh/DTTz8hOTnZ6zG7du2CyWRCWlqaD2pIgoWD1xehZ6JtoPzlbdzaWLxz6Nyfw893qnF9ThsjBFscQPPsEK1ojkl3fm3ZKSoqwuHDh51fHz16FLt27UJSUhKqV6+OYcOGYceOHVi2bBnsdjvy8vIAAElJSbBardi4cSM2b96Mnj17Ii4uDhs3bsSkSZNw3333oVq1av76WCQA8Vt25KztuPXYJWw8chGP9aiHCLP43wQBkp+sWyAi1Z2kf4Lyjdejb66DlFgbeuak6nwWPepN0YNcdKVIoPJrsLNt2zb07NnT+XVVHs2oUaPw6quv4ttvvwUAtGzZUnDcmjVr0KNHD9hsNixevBivvvoqSktLkZ2djUmTJgnycQgBAAc/2JGx/13zNgIAUuNsGNFefMkAfuuE3cGufx0gEZBCngJAY9fGulG6zWLGa4Ob6nuCICVsiZL3s0TLRRAxgdL67G9+DXZ69Ogh+Rept79WW7dujU2bNuldLRKC7G7dWPJuAEcvXJXczr+RVDgcMJvMquqnlV6BiFvODu8NvZOg+efyVQtZMNz31TycAqUbKwguLwlTAZ2zQ4heKhS27Dj39RJF8B/SFXb/PWX0WQjUt/gtOzTnyQ3BfCWoGyswCJL//ViPQELBDgkLDpecHbm87ct/YPs12NGrZUfia727scw+Go2ltehgmGeHRmMpJ5GKR0IQfbtJWOCPPNezO0bQsuMwZi4fOfRZCNT9KSkcjaX5FKJlG4lfbTUtSP5cLkL2MfzPRd1YkkbfXActshJxS066v6timGCehdsoAT/PDiF6cB2NpRd+EFXVVeaLm8uEnvUwe80R59e6fSYf3hj5wVWsjW5FVahLz1iv3t7E31UgfkB3GBIW+PPsXC2twOw1hzGgWXU0qi49SaW3GIKf+OxgDNfKKnD+SqmWqspixAPR48IX/ARlA/pzXrujCS5fK0edlBjdy64SdGsiqmnZoW4swiMcnEc/EAAFOyRM8Ft2Zv54AIu3nsS/Vx/GsRkDJY/z9nxnTNhi9M5PhzTVUy6jWo98fWO8v1Mdn56PEBKeKGeHhAV+y86eUwWyj/tow1FU2MVzcewuo7x+O12oqn5KuebX6NHq4i2ACoI8XUMY0aIlhXIsiFa0EKg7CnZIWNCyNtaqP85JlHvjNWPMZzcW19PolrIjUf9gGJXkiSBBOURv/KH6uQjRCwU7JCy4tsAoUVoh3rLj2o3lK64LkOpxbm9dWMG4sroeguFTB0peRjBcKxKeKNghYUE4Gku/W7LdT80drn/J6xWISD0yg7VlR88w4JVBjVE31bhkakL0QC197ijYIWFBS1Aidd/g9445fBgNGHEvC4cbpJqPmJMR53w9pnM2Vj/dQ7f66EXwvaN5dghxQ8EOCQsODTk7UkGA68zMvlp0z2TS3o315rDmbu9J1T9IG3Y0mzW8FYa3zcL3T3T1d1UIkYUmFXSneuh5fn4+tmzZgnPnzsHhMnPsAw88oLlihOhJS4KyFH5rjj+DATXnvrttFr7e+Rd+PXJR3jlCINpRE4xmJETiHx4Cw0ASdHMJEeJjqoKd7777DiNHjkRRURHi4+OFi45xHAU7JOBoWbZKKvnTNRfIV88Zt5ydEAhEiHqCII5+FsKeYFJBatoBoLIb6+mnn8bYsWNRVFSE/Px8XL582fnv0qVLeteREM0M68YSrLkFlFbYVZ9HCavbKobqPp/rZ5O+L9JTlBASnFQFO3/99ReeeOIJREdH610fQgxh1KgpfjfWiUvXsOlP3wT7CVEWwddqP56SycdCofUoGP7GVVNH6sYiQpyHV+FNVTdW3759sW3bNtStW1fv+pAw8kdeISxmE+qlxhp+Li05O9KjsW6U+5+Nx1WfQynXYEctt5YdiX1DINYJCnGRFvRtko5yO0N6vE3WMYHSU0E/IyRQqQp2Bg4ciGeffRa///47mjVrBotFeOO9/fbbdakcCV0FxeXoN+tnAMCffx/gNrpIb1pWPZd6kBg1f483kRaz4GtdJhX08sT09bIJ4SIzIRKnC0qQmRDpfO/9+9v6sUYk2AlzdvxXj0CiKtgZN24cAGD69Olu2ziOg93um7wFErzOXylxvnYwBpPBja0VBo3GYi45O75i2KSCIX5jDMTPt3BcR8xdexiP9rhJdRmBkoQaGLUgxJ2qYMd1qDkhyt24LfoiSLBr+pmVOxpLwykUch0hpjpnh5Pft0/tOsbITonBm8Na+LsaJIQI5tmhEBSAigTl8vJyREREYN++fUbUh4QJwUhZHzxFjWrZ4efs+HQGZbeWHd1KFt0SCr1YdOMnJDwpDnYsFgtq1apFXVVEseIyzz8zvlhg0rih576PAG7JSXN7T/1oLN5rr6OxQiDaIYSEJVVDz1988UW88MILNKcOke2jX46i0dQVWLbntNs2XzxDtTTsyF0byxc2TemF/3ugrVud1AaMSubZoVCHkOAgnOjXjxUJIKpydt577z0cPnwYmZmZqF27NmJihKsA79ixQ5fKkdAxfdnvAICnFu/Cbc0zfd6ZoCWgkkr+9HXOTkbViB0DLmA4dPHQjZ+Q8KQq2Bk8eLDO1SDhoioe4AcQvugK4rd8KG0FkTvPjj+6tJx06Mby9LUe5yA+Fnw/hkRnnMjrcKYq2HnllVf0rgcJE57yPnwRIxh1DsFCoP4cjaW2HAXN3fQgI4QEK1U5O4So5WzZ8fCeoefVEIlITyrIO4cfwwG1n8+tZUfiw1KCcpDw45/y1IoQGDhq2nGjqmXHZDJJ5zHQSC3iBf/Hx6jun2tlFRj/yXbUS43BxxqWcpBM2vVXy45hQ8/FUahDCAlWqoKdpUuXCr4uLy/Hzp078fHHH2PatGm6VIyEJk8BgdwgweFgKLM73JZKEPOfjcfxy+EL+OXwBVXnk0OQoKxfsV65jcZSPamgsMxQ/yOQEpRJOBD+XtMPPaAy2Lnjjjvc3hs2bBiaNGmCJUuW4MEHH9RcMRLaBL+AMh/UI/5vEzYfvYSdL9+KajFWr/tfFZnXR08Of60XodGNm6H8GyH1YhFCgpWuOTsdO3bEqlWr9CyShCjBDMoyo4TNRyvndfpp/1l551BcK7FyxEviz7Pj2xmU9UlQFhbqbZ4dinYICQb8exa1ZlbSLdgpLi7Gu+++ixo1auhVJAkTSifmk7voodhuih/ZMmdQ9mcoIMwdkl8TJTfCUGjZoSZ9QsKTqm6satWqCR44jDFcuXIF0dHR+PTTT3WrHAkPSkf5yH1cmXzwJ41wUkH/rY116nIxpn6zDzfXS0afxhnej3f5v/I1JxkMhECsQ0h44Dy+DGuqgp23335bEOyYTCakpqaiQ4cOqFatmuxy1q9fj5kzZ2L79u04c+YMli5dKpiwkDGGV155Bf/3f/+H/Px8dO7cGXPnzkX9+vWd+1y6dAmPP/44vvvuO5hMJgwdOhTvvPMOYmNj1Xw04gdKH6JyYxj9urHE+Stlx7VOu07mY9fJfHyy8TgOv9FffjlKLhJFO4SQIKUq2LnllluQlZXlsTvhxIkTqFWrlqxyrl69ihYtWmDs2LEYMmSI2/Y333wT7777Lj7++GNkZ2fj5ZdfRt++ffH7778jMrJy2vyRI0fizJkzWLlyJcrLyzFmzBiMHz8eixYtUvPRiB8ozXWR22KjV8NOIC0XIYfa9bo4Lzk7oSDUPx8hxDNVwU52djbOnDmDtDTh6ssXL15Edna27Hl2+vfvj/79Pf8VyhjDrFmz8NJLLzlHf33yySdIT0/H119/jXvuuQf79+/HihUrsHXrVrRt2xYA8O9//xsDBgzAP//5T2RmZqr5eMQHBIEBq1wRPcoqb0i57JYdkR317Dbz1xIRWldir7o2SnJYKEGZkOAjN8cx1KlKUBZ7WBQVFTlbXLQ6evQo8vLy0Lt3b+d7CQkJ6NChAzZu3AgA2LhxIxITE52BDgD07t0bJpMJmzdvFi27tLQUhYWFgn/Ef3acyEejqSsw/bvfdS3XF7/jgZKgzKd6zh2DyiWEEH9T1LIzefJkAJWR4tSpUxEdHe3cZrfbsXnzZrRs2VKXiuXl5QEA0tPTBe+np6c7t+Xl5bm1LkVERCApKcm5jye5ubk0+aGf8VsJ3vzxDwDARxuOYuqgxl6PlT0aS6esHelWlBuvfbucgnilXCdRVHb0Db1yhL9boRDr0N+4JNzQz3wlRcHOzp07AVTe1Pfu3Qur9cbEblarFS1atMAzzzyjbw0NMGXKFGfgBgCFhYXIysryY43Cj2s3lhJyf3l1y9mROKO/cnakPtu4T7bJPl4w0yrHCb5+9fYmgmNobSxCSLBSFOysWbMGADBmzBi88847iI+PN6RSAJCRUTl89uzZs6hevbrz/bNnzzpbjzIyMnDu3DnBcRUVFbh06ZLzeE9sNhtsNpv+lSayaYh1ZCcom/SaZ0cCvxvLX/k7RD7KXyDhhn7kK6nK2Zk/fz7i4+Nx+PBh/PjjjyguLgag719+2dnZyMjIEMzIXFhYiM2bN6NTp04AgE6dOiE/Px/bt2937rN69Wo4HA506NBBt7oQYykfjSVvP19MIOfwV8uOYeXSPDuEkNCjajTWpUuXcNddd2HNmjXgOA6HDh1C3bp18eCDD6JatWr417/+JaucoqIiHD582Pn10aNHsWvXLiQlJaFWrVp46qmn8Prrr6N+/frOoeeZmZnOuXgaNWqEfv36Ydy4cZg3bx7Ky8sxceJE3HPPPTQSK8AxDS0i8kdjKSpWlNQoJHuQtuZ4Cmpc33FbWT04PyohYY1mDa+kqmXnqaeegsViwYkTJwRJysOHD8eKFStkl7Nt2za0atUKrVq1AlCZAN2qVStMnToVAPDcc8/h8ccfx/jx49GuXTsUFRVhxYoVghFfCxcuRE5ODnr16oUBAwagS5cu+OCDD9R8LOJDgm4sGQ9RYauh3Hl29OnHkqqfIEFZWbGa6NUd41pMqDd5h/LHi7k+dUOLmon+rQghAUhVy87//vc//Pjjj6hZs6bg/fr16+P48eOyy+nRo4dk1xfHcZg+fTqmT58uuk9SUhJNIBiEBDMPywp2bryW+0CW292lhcNfy0UYUaZb4BPKoUHo2f7yrbhWZkdSjNX7ziR80K8xAJXBztWrVwUtOlUuXbpEib/EEPzuItkzKIu8/+eFq4rOLRXCCObZCaZunnC6AYbJZ420mBFpkTcxJyHhRlU3VteuXfHJJ584v+Y4Dg6HA2+++SZ69uypW+VIKFPWIsIPKuQPPdfnKSdVP2E3lv8WAtWlTAiHnodMjKCiVZCoUz0xyt9VIC7oZ76SqpadmTNn4pZbbsG2bdtQVlaG5557Dr/99hsuXbqEDRs26F1HEoKULKA5f8NRpMTeaDH0dTeW3BYbNS07yx7vgtv+/Yvi47QmHdL9j+hp/ph2WLX/LEbfXMffVSHEI8XBTnl5OZ544gl89913WLlyJeLi4lBUVIQhQ4ZgwoQJgjlxCJFDKkjYcyof01yWkZD9l4pOf9LIHS2mpl2naY0EFUdp5/HScMIgKhT/IqQ8JGP0bJiGng3TvO9IiJ8oDnYsFgv27NmDatWq4cUXXzSiTiQM8AMDqWAir6DE7T25rRpKHmvHL17F05/vxiPd66F3Y+ESJfJbdoKvG4uGpRIS2ug3vJKqnJ377rsPH374od51IWFEbjeWw8NGPefZKbc7wBjDhEU7sO34ZTzkYakFI1t2/E6wXITL8hGhcpsMkY9BCFFPVc5ORUUFPvroI/z0009o06YNYmJiBNvfeustXSpHQpfcZF5PrSXyl4vwvl/nGavRpX4K9v1VKLqPp4DLk2AajRUygYwcQfR9IURv1HVbSVWws2/fPrRu3RoAcPDgQcE2urBEKbmT9lXhOGDXyXykxtlQQ2L0h5yfxHNXSvHVjr+81VBGScBRhUPalbqvYy3n64Qoi+7lcxBeM/pVJr6y8KEOmPLVXswY0szfVSEhSlWwU7UgKCFqCScVlBra7b7t8LkiZ9LysRkDRY/V62Ett2XHSPPua41+TW8k/1dPiJTYmwhQ0BbwOt+UgvXP0bQlRqAf/0qqcnYI0Upuzo6nbXtOFcg6h16tjIG4mnmEWduvrqdLw3EhOs8OISTsUbBD/E6qZcfTNtkJymor5CIQWnY8fZpIC/36EkKkUXd0JbpbEr/gJyhLBROeWlVkLxfhgxmU/WnV0z3wzj0tJfOW6qfFSpYhufZ5qNwkA/PbRwjxIQp2iF/IztlxuL8ne05BZVUSFQixjqe4rUZiFO5oWQNRVs/rIaXEWtGmdjXP5cl8jxAS3MJq5KUECnZIQNPSsmNkHQKJVSR/x7Xa+6b1db4Wa/WieXYIIaGIgh3id5IJyh42mgz+qS0oLvdaB1+Tel5bI0SCHZevY23Sgy+pb5+Q0EO/15Uo2CF+IezGEt/PU6sKv1VCMrlZVc2AwbOFi9kGa8uOgzHRG13V264tPJ7m2alahLV2crSGWhJCiP+ommeHEK34CcqeApYrJeX4YP2fKCqtcNvGX83cwQCzyANdbWKx6+SAgRDrSCVbi7V0ORQOIxPrtlrycEe8v+4IJvS8SVF5hBASKCjYIX7hbZ6dv3+/H59tOenxWH7OToXDAbPJc4KuXjGK3KUtAo2aII0fVFW9qpcaizeHtdCnUoQQ4gfUjUV87tiFq7hr3kbn1/xuoqFzf8XeUwXYfVJ84kB++4PdQ+vFvr8KMHTur9h69JIu9Q2EeXakut0r7J4ryKSO9DipoMJKEUJIkKCWHeJzTy7ZhTL7jTHl/BaI7ccvY8T/bZLMD+G3PngKdu77cDPyr5Vj+/HLutT3qoeutEDCv5Z8cnKNpOIbWueOkOBHv8aVqGWH+NzFolLJ7UWlFZK/oPxtnoKd/Gvlbu9p8fry/bqWp4bU9Sir8BzsSMU6dP8jhIQTCnaIz7k+hJX2EvETaSsCoY/Jz8o1tOwQQkJbyMyXpREFO8TvPK5/JfELKlhqIkyCHcmWHZFgR2ms43oOukUSQkIFBTvE51yDG08PZamHO3//cGnZkQr+xLqxJOfZoY58QsIC/apXomCH+JxreKK0u4W/v6ecnXBTLjkay7OqG6DU8hB0kySEhAoKdojPuQY3nuIVqedsWAY7qhKUvV8bX68zRgjxLfoNr0TBDlGk3O4QTYiVS1ZDjsRDOBy7saS8NLARAKBvk3TB+1KXpurqSgU7lNhICAkVNM8Okc3hYOg8YzUcjGHzC71hNql7GGoNT/gP8VAecRRlMaO43A5A+q+ze9rXQrcGqbA7GH787axgm7fvEP9bSI08hJBQRS07RLaC4nKcu1KKC0VlXufKkSInPpF67vK7Z8RmDw4FafE22ftmJkapClYkA1YKfggJejQYoRIFO8QPZMzsK/H7GS45O8IVyL3fsJTc1Kr29bQWFiGEhBoKdojPae154sc39hDoxvr0wQ4e31f6F5maXkXJhh2KfggJevRrXImCHeJzsvKTJbYJW3a0JUsHgo51k7zuI+eGpSahmJ+gTM3dhJBQFfDBTp06dcBxnNu/CRMmAAB69Ojhtu2RRx7xc62JFDlDoqWPv/E6lHN2lPIUq4hOKnj9f6mcHQp9CAl+9DdMpYAfjbV161bY7Xbn1/v27cOtt96Ku+66y/neuHHjMH36dOfX0dHiK2YT/5M38lz8N1TQsqMhcDJx0sOzfUVePo6cctScm/da+eGEEBIUAj7YSU1NFXw9Y8YM1KtXD927d3e+Fx0djYyMDF9XLaxpiRG0jsYS5OxoiFbMJg6OAGgZEvusSlvAlHRjVQU5Zql5duhPQkKCHv0eVwr4biy+srIyfPrppxg7dqzgG7hw4UKkpKSgadOmmDJlCq5du+bHWhJvtHZj/XzovPO1lkkFA/0mIBwppU/rD29vAIDJxM/ZUXI8IYQEj4Bv2eH7+uuvkZ+fj9GjRzvfu/fee1G7dm1kZmZiz549eP7553HgwAF89dVXouWUlpaitPTGPDGFhYVGVjtk8LuPtDwXNU6gjPxr5TfqpKVlJ0Ce7npVQ83SD9IzKBNCSGgIqmDnww8/RP/+/ZGZmel8b/z48c7XzZo1Q/Xq1dGrVy8cOXIE9erV81hObm4upk2bZnh9Q41uHT6yurHkPWq1tOyonABad7rl7Hh8T/pA4QzKAXJBCCFEZ0HTjXX8+HH89NNPeOihhyT369Chcs6Sw4cPi+4zZcoUFBQUOP+dPHlS17qGKn7vk6acHc01uUFLzk6oLYKp5PNU7SrZshNal4cQEsaCpmVn/vz5SEtLw8CBAyX327VrFwCgevXqovvYbDbYbPKn4ieVGC9M0bImlaycHZkPWi3BTjA9zGVVVc2kgoHSvEUIIQYKimDH4XBg/vz5GDVqFCIiblT5yJEjWLRoEQYMGIDk5GTs2bMHkyZNQrdu3dC8eXM/1jhE8Vt2NDTPaJ1UkE9bsBNaD3o1H0d6aazQuj6EkPAVFMHOTz/9hBMnTmDs2LGC961WK3766SfMmjULV69eRVZWFoYOHYqXXnrJTzUNbQ6durHktArJfXCH8qrnnOgXninqxrr+f6AkaRNCiJGCItjp06ePx66PrKwsrFu3zg81Ck+CbiwNLSryerHkPYSrqrHvrwLERUagdnKM7HqE2nPeY4Kyl88o1Y0VateHEBK+giLYIYFBr0YUrUPP+RwOhrOFJbjt378AAI7NkM7pEpxD9p7+p/c8O1X7UkBDCAkHQTMai/gfP0jRFPjo2PPkYAxHzhepOjasR2NVTSoYYteAEEI8oWCHyMbvutI0GktGtCM/ZwdQu/B5MD3n1dS1VpL3NeIoZ0edwS0r5/pqV6ean2tCCJGDurGIKkavjSWXnTENgVeAP+gVVo8ft8TaIvDfR2/Gv1cfkn2Mkm3h7o07m6Fbg1T0ykn3d1UIITJQsENkE0wqqKllxzu5CcqMMcHK50rqFWoPc36X1B0tM5EaZxO9is6FQGmeHVVibBEY0rqmv6tBCJGJurGIbPzuJ20tOzp2YzmYoLxR87fKrkeoPebVfB7ptbFC7QoRQsIVBTtENocPW3bksrvk7Kw/eF58Zxeh1rKjZpJEmkGZEBIOKNghsjFBd5GWcnSojLMsYTeWEqHWcuEpbhELgKrelZxBObQuDyEkjFGwQ2RjIq/lUPrglNtKYXfpxlJ2jhuvm2TGqyojkPCvmdwrQkPPCSHhgIIdIhs/plA6AsqoR6qDCbvXlODX6e93NkPLrEQ9qgQA6Fo/RXMZvghDqBeLEBIOaDQWkU2vbiw55D6D/7HiDwxolqH9fFzgPfiNXKi0quxwaNkJte5KQohy1LJDZNMyg7KRD+7v9+apOo5fJw6crg/+YFlRPRyGnsuZxJIQEtoo2CGyCebZUfgAUfpIXadgVJUeOC48Rya5Bnj8SxDCC8oTQsIMdWMR2QTz7Chu2dG5MjpwrZOesU4AflyBqs/uGuDVSopGtwapiLNFwBpBfwsRQkIDBTtENv58NqHwVz8/2KnM2QmsEEXTXEZeDq2fFgvAPcDjOA6fjG2v+ryEEBKIKNghsglnUFbajcVB3+kEteMnrpo4LuBan/TI+3Et4ruJXfDppuN4um8DAIEX4BmBEpQJIRTsENmEQ88VHhyAzxvXlh1ft1b5I0WoWc0E/GNYc7/WwdcoQZkQQp3yRBUtXSyBghO85jSsnq7Oz8/f4tPzeRIOLTuEEELBDpGNHwwEf6jjMvScUz85oeeyve9TIzFKvxOqFA7BDnVjEUIo2CGyCYaeKx2NpW9VdMG5vtYz2NGvKEOFwzw7xBhWMz0+SPCgn1Yim3BSQYUJyoH4THXJ2VG7oGhgqvws3lo1AvL7QoLConEdUCspGvNHt/N3VQjxioIdIhsL8m6s9+9vI/iac/mqQs9+LB34Ig6pFm31wVn8ixKUjdG2ThLWP9cTPXPS/F0V4iNZSdH+roJqFOwQ2eQuF/FXfjFm/vgHzhaWON8LhLwJDpV/jVbh56uYOMChMtgZ2Kw6+jcVrs8VLMtFtMhKxOO33IR/DG3m76oQQgLUZ+M6YkT7Wni6TwN/V0U1GnpOZOO37EiNXHrgw804cv4qfj50Ad9O7AIgMLpLOI7DzfVSeF8Lt9lVBjtZSdGYeMtN+GGfujW6/O3pPg39XQVDBUKgTUgw61QvGZ3qJfu7GppQyw6RzVuC8tnCEtw9byOOnL8KANhzqsBHNZNH6pHHAaqDHSBw56sJhCCTEEL8jYIdIpugG8tDHkTu9/ux5dglz8cGQNqE64Of/xe/1gTlcBjCTQgJDi1rJgIAoixm/1YkgFA3FpGNCaMdN0WlFeLHBkCSqFuww+/GAqc6Z8dT2XpMuqglfgqE4JIQ4h/VYqzY8fKtFOzwULBDZHMIcnbct1sk5t0IhIevVO6GlpYdBkYtO4SQgJIUE/ojLZWgbiwimyBnx0NLTYRUsGNEhZTysML3jddAhV1lLRl1YxFCSCCjYIfIJlj13CUu+H8//4mfD52XOtjvXMMRk8toLC1rY7kmKAfAxwUQPDM5E0KIkagbi8gnWPX8xhdbj13C68v3eznU/49/19YXYc4ONE0qGCzz6hBCSDiilh0im0PQjXXDmYISt31dBUTOjpfRWFoSlAkhhAQuCnaIbILWGd5LOW0agRBGuCYou47GUp+gbAwtk+EFQnBJCCGBIqCDnVdffRUcxwn+5eTkOLeXlJRgwoQJSE5ORmxsLIYOHYqzZ8/6scahzVuCsvSx/n/6urfsCLepnVTQ02fT4+NSzxghhOgjoIMdAGjSpAnOnDnj/PfLL784t02aNAnfffcdvvjiC6xbtw6nT5/GkCFD/Fjb0LTzxGWczi8WhDcOh7Iy/B/qGDuDcqCigIkQQoIgQTkiIgIZGRlu7xcUFODDDz/EokWLcMsttwAA5s+fj0aNGmHTpk3o2LGjr6sakv7IK8Sdc34FAMwf0875vtKwIAAadtyjHcHQc/VrY3miR0kBcc0IISQEBHzLzqFDh5CZmYm6deti5MiROHHiBABg+/btKC8vR+/evZ375uTkoFatWti4caNkmaWlpSgsLBT8I57tOJ5/4wvB2ljB9yR2y9nhv9bQjeVJMF4fQggJVQEd7HTo0AELFizAihUrMHfuXBw9ehRdu3bFlStXkJeXB6vVisTERMEx6enpyMuTXn06NzcXCQkJzn9ZWVkGforgJphbh/dabGSWxzIC5MEv1aXDQcMMyh4Ocx2KPrhlpqqy1QqEof6EEBIoArobq3///s7XzZs3R4cOHVC7dm18/vnniIqKUl3ulClTMHnyZOfXhYWFFPCIEF/pnOH4xat4+vPdyEqKll2GP7nGOvxqcRynup5yDnvjzmbo1iAVu0/m4+ONx2WVS/k2hBCij4Bu2XGVmJiIBg0a4PDhw8jIyEBZWRny8/MF+5w9e9Zjjg+fzWZDfHy84B/xTJCU7BL4TFqyC9uOX8bSnX/JLsOfqlpbGqTHAgAGNrvxc6J3XOHamhVji8CQ1jWREO3b9WposkNCCAmyYKeoqAhHjhxB9erV0aZNG1gsFqxatcq5/cCBAzhx4gQ6derkx1qGGN5Dm/8AZwDOXSmVWURghDtVz/1lj3fFlhd74aa0WME2i9n4wMDbGe7rWEuX8wTIJSeEkIAQ0MHOM888g3Xr1uHYsWP49ddfceedd8JsNmPEiBFISEjAgw8+iMmTJ2PNmjXYvn07xowZg06dOtFILB0xkdcOxmTPOBwoz92qAMAaYUJaXKRwBmVw+PTBDqiVFI26qTGG1cFbQ0uszWLYuQkhJFwFdM7OqVOnMGLECFy8eBGpqano0qULNm3ahNTUVADA22+/DZPJhKFDh6K0tBR9+/bFnDlz/Fzr0CKWs8OY/LWkAqWVQWq0FWcCOtRNxvrnemLad7/hz/NXZZer5PNVT4iUv7MG1HtFCCE3BHSws3jxYsntkZGRmD17NmbPnu2jGoUfJtGNJXeV8EAZGSRVXy2xgZLPN7R1Tew/cwUd6yZrOKN3gRJgEkJIIAjoYIf4n1g3FmMstFp2fNQUEmE24dXbm/jkXID+ideEEBKMAjpnh/ifVDeW3En4fjsdGJM2us2jw3l8qWkBTq2o+4kQQvRHwQ6RJGzZEU4wKDfY+fv3+3WulTpSo8IEK6DLCDge7lbXy7nk1soYAdKYRgghAYGCHSKb2pYdqzkwfszsLouXKmnNebZvQ+frDX+7BX/rn+P82qjARpdyqaWIEEIo2AlVBcXl2HD4guzh4WL4rSEOwWv5wU7zrARNddCLdM6O9LFRFrPzdY3EKMNyfPQqlWIcQgi5gYKdEDVs7q8Y+f82Y+FmeUsTiBFrXVCSoBwofSqSo7FE8nfkHOuJv0egBcglJ4SQgEDBTog6dK4IAPDNrtOayhHk6ShY/JNPz9XEtZAeei7dFqI42FH5kSlBmRBC9EfBTojTM8xwiMy5443sFiCDye3G8hRwKP0IaoMWftClpXWoQ3aS6mMJISTU0Dw7RBI/ppn8+W6P73ujtFVErmirGdfK7Krrwc+74UTeryIVKHkL/H58qpu8Curg5+d6YtfJfAxsVh2Af4fRE0JIoKBgJ8SpWYSzpNwOW4QJHMeJti0EQjdWdkqMojl8bq6XIrrNW8Kx0uvI371qlXWl1MSIWUnRyEqKVnU+QggJVdSNFeKUPi9PXb6GnJdX4NFPd1QeL1KAktYao1p2AHndRS8NbIRtL/VGerxwXSpOxusqrsPWveF/ZLUjt2wW+vUkhBA90N00xCmNMz7bcgIAsOK3vMrjRcIlJeVW2I0JdhgDTDICCZvFjJRYm+Q+nJdox232ZX49vNZAPo4DZg1viTrJ0Xjr7pa6lEcIIeGOurFCnNIHsWuOh+jQcwVlSgUKWjAAJg7wlrUj53mvdzeWWmnxkRjcqgYGt6rhk/MRQkg4oGAniCzfcwb5xWUY2aG2YeeQ3RKgpBvLoJwdxtj1IEW6fD1aN6S64vSIg/7vgbb4+dB53NMuS3thhBBCBCjYCSITFlXm0XSrnyo/CVXhk9g1LhBr0VASvxg19JwxwCwjkhEbkSR2qKf9FefsKGxTu7VxOm5tnK7sJEQW6sojhFDOThC6fK3MuMI5md1YAZCgzMBgkvEg0+Nh56tuLKI/+tYRQijYCRJqu4KU5+zIO764XF5TB2MMV0vlz4WjhNwEZbE9xFp87vSQLyM5z46HqxQoD1hq1CCEEAp2goba1hGlh7nGDmLH/2PFH7LKe2zhDqw7eF5ZJWRyMCar1UZsH7GupoYZcdjyYi/USIxyvmdUkjUhhBDjUbATJPgNC0qeu0pzR9xGY2kcWP3DvjxNx3tTo5r33CU1swinxUXCzOsjk7rmnrZRngghhAQOCnaCRKC17AQCBqBT3WSv+1kiRBKUFQRBSq9/rM2iaH9v4iJpLIFaFHgSQugOaqCZP/6BU5eL8fStDVErWdsU/oJFOLVWTILc0VgBgQE51eMkd4m1ReCWhupGOfFbtZQueVE/PRZNMuORFi89maE3M4Y0w+n8YjTJTFB1PD3oAztgJ4T4BgU7BvphXx7+PH8VI9rX0iHYUXec1padQM5VcTCGmtWiJPeZNbwlEqI9t7LU8jJ8n//R22cnYeHmE573u/4/f2HSVlmJ6NMkQ7J8Oe5pX0vT8a2yqmmuAyGEBDsKdgwUH1n5kC0oLtdcllGLabpynUnYR6cVNfrmOljw6zGP2xiAzATpYCfCLN60USs5Gp+MbY+kGKvXegxqngmziUPzGomi+6x6ujs+33oKdVKiA2bOnF6N0jBnZGs0qh7v76oQQojfULBjoISoymDn/JVSzWXxu5OkupaKy+yIsppv7KvwPKUVN4aUl5TbDZv9WK4O2UniwQ6Ds2XHGmFCWYX7cHiLWTotrVuDVFn1MJk43NY8U7QeAFA9IQpP9q4vqzxf4TgOA5pV93c1CCHEryhB2UDx14Odl77eh+IybXPNyIk5fj1yAY2mrsDsNYed7ynJuSksKce7qw45v2726o+4eNXACQxlkMo5cTCGCLMJe1/tg60v9Pa4T4ScWQdFyL10VonWI+J/lLdECKFgx0C2iBuXd39eoaay+N1YYs/gSUt2AQBm/njAa3kl5Xb8fOi8oDXk54MXBPuU2xl+2HtGcV31Jf6kqgpG4iItonk5EV5adrR4YUAO6qXGYOItgdWaQ4QCOO2MEOIjFOwYqKikwvk6zqatx5DfQiPWtXS20L27TOxG//Tnu3H/h1vw+vLfne95Ska+qrFFSiutf5VbDGx1Gd+tHlY93QOpcdpGXBFCCDEWBTsG4icmax3VxI9v9EhWXn69xeaTjcdvnMPg/Bw1K3pLhSpyuui85eyQ0EfdWIQQehIY6JacNOfrCru2QIIfLHmLSWIECcryz2v0iK8eDeUlA/O5jg7jk1NdLS07AT3HECGEENko2DHQqJvrOF9rDST4rS7eZvONUdllZvScOlVD8ZXghyr1UmPw9vAWzq/lBHIRJvU/4hTqEEJIaKBgx0DWCJNz4jqtgQRT0I0VaeG17Cg4rdHdWDZeveTiN+zE2CJwZ6uaGNmhcqK9Z/o09Hq8WcNoLBIaqIGOEELz7Bisauiz1pYdfrDkKXDij6qKsqibZ0duFbvWT8HPhy5439GFmsCDH+xEX++ee31wU0y85SZU9zKhICA9qaA39JAkhJDQQC07BjNdf8BrzdlxeJlU8GrpjZFfkfycHQ/7ltvdJ98D5Lc+pcdHytrPldo5b94c2hzZKTHIHdIcQGUej5xAB9DWsqN1xXcSGChBmRAS0MFObm4u2rVrh7i4OKSlpWHw4ME4cEA4h0yPHj3AcZzg3yOPPOKnGruresCrXbW8Cj9o8RSrFPGCHf693dNZ//k/z/PwyO3GUvtRTCqeOhw43N0uC2ue6YHslBjFx2vJ2SGEEBIaAvpJsG7dOkyYMAGbNm3CypUrUV5ejj59+uDq1auC/caNG4czZ844/7355pt+qrG7qpaFCpdA4uiFq5j54x+47DJDcbndgbdXHsT245cF7/MDHE9dYlfLbgQ73gKrj0WWX5DT1da/aQbGd6vrdT/daPyrXFPLDjXsEEJISAjonJ0VK1YIvl6wYAHS0tKwfft2dOvWzfl+dHQ0MjK0rzBtBLMzZ0fYHDN49gYUFJfj0NkifPBAW+f7H/96DO+sOoR3Vh3CsRkDne87BEPPpbuxBEGLhwe22ENcTuvT3PvaeN1HTGmF8gkKtfZARKlIiq5CsQ4hhISGgG7ZcVVQUAAASEpKEry/cOFCpKSkoGnTppgyZQquXbsmWU5paSkKCwsF/4xSFeyMXbANv50ucL5fNeHglmOXBPv/kXfFYzl2L0PPr5R4DnbkPLDfX3cED3y0BdcMni25pNwBa4SyHzmpeXbEmE0cFo/viC8f6aT4fIQQQkJPQLfs8DkcDjz11FPo3LkzmjZt6nz/3nvvRe3atZGZmYk9e/bg+eefx4EDB/DVV1+JlpWbm4tp06b5otqCpNzxn2zHhr/dItjuGreI5c14G3peUm73uN1TgrLrO7k//AEA+PN8kcdz66Vx9XhEWcweVyfnG9K6Br7a8RcAdS070RYzOtZNVnEkIYSQUBQ0wc6ECROwb98+/PLLL4L3x48f73zdrFkzVK9eHb169cKRI0dQr149j2VNmTIFkydPdn5dWFiIrCzlSxnIwU/KPX/Ffe0q11YasRFR3rqxynmjvcRGWzmJNPfkXyv3vEEHO16+FQnRFkRZzIJlNDwx866ZmpE00Tb1XVd8lLMTGmjJEEJIUNwFJk6ciGXLlmHNmjWoWbOm5L4dOnQAABw+fFh0H5vNhvj4eME/o/DneTGbOFTYHfiFN0fNlZIKQWuOWJIwPwhaf/ACKlwCmgpeThA/8PFUmtiQam8tLmpN6Z+DpBgrACDK6j0Q4V8zTkXbToxVrxieop1Q8GDnbDRIj8XkWxv4uyqEED8J6GCHMYaJEydi6dKlWL16NbKzs70es2vXLgBA9erVDa6dPGbe0GezicOCX4/hvg83C/b5745TztdiScL87qilO//Cu6uFwZxYy46n4sRaLMq8tQip0KluMh7ufqOFLVJGwjB/BJU/W3YapMfpUg7xr4RoC/43qTue6FXf31UhhPhJQAc7EyZMwKeffopFixYhLi4OeXl5yMvLQ3FxMQDgyJEjeO2117B9+3YcO3YM3377LR544AF069YNzZs393PtK/En8DWbOPz3ei4KX9UK5IB4y47r259uOi74ukJJN5YPRbu05ERZxH/kaiRG4fsnugq7sVSdU5+WnbeHt8TwtllY9ngXXcojhBDiHwGdszN37lwAlRMH8s2fPx+jR4+G1WrFTz/9hFmzZuHq1avIysrC0KFD8dJLL/mhtp7xW3YiTBziIt0vOX/iO7GpblyDIKluLH7g47of4NvOGdduK6lurJnDmqNxZrzgmqmJdlwDLLXS4yPxj2GBETQTQghRL6CDHU8jifiysrKwbt06H9VGHf5oLLOJQ5yHFcktvOYfsdFYbonMvP1KK+yY+s1vzq/53VH5HpKBvV1XPbnmz0jNe1O1UGjg5OwQQggJBQHdjRUKzK7BjoeWHZOJQ0m5HaUVdtG8Gdf4pMLBUHx9Xpxvdp1221blWpndLfFYj1BHbi6Na0vOg13EZ1+OvN7FZVI5Gqt7g1QAwOjOdeQfRAghJOTRn8AGM7kEOzEeWnaW7zmDlb+fBZh4krBrN1ZphQONpq7Aw93qIjMxSnLfy9fKBIt36tGwE2Uxy5qE0LVLqVO9ZGya0gsdc1d5LBMQtoYpadf5cFRbXLxapnqhUkIIIaGJWnYMxu9+ijBxojk5ZRUOydFQJy97nhX6/fV/orhcOui4UHRjfh+5i316I3cZBk/5MxkJnoORqpFawtFY8sOdCLOJAh1CCCFuKNgxWCkvEDGZOFVz2TDG8OLSfaLbZ1yfAVnMhaIbi40u2nJC8fk9kTOEHACivOTPNKuRcGNfTy07WhfHIoQQEvaoG8tgpRXCUVJKFsN0OBhMJg4nLkmv9eUNf8biL7efkthTPrkjnsT2m3Z7E1y+Voaikgrs/atyzbCqAMqkshuLEEII8YRadgxWWn4j2CmtcE8WllI1a/K+v7QtVFrIC3bkrGwuh9gQ8kbVhbNRiwU7o26ug6d6C2e0tV1ftDNCZTcWIYQQ4gm17BishNeSc7awFH9euCr72Ao7g8UMrzk53hQUl2PNgXN4Y/l+HD6nz2KfYt1Y/EAF8J7bw49lqlp0+Dk7es2ZQwghJHxRy47B+C07ABQFG1UTBWpds6qwpByzfjqkW6ADiAcxZpdgR81sxvwy5CZCE0IIIWIo2DGYkhwdV//630HNZQCV3VhnC0o0leGqWrTF4/uuwY6chT+lyqCWHUIIIVpRsGOwUg2tMgt+PQZAh5ad4gpcK6vQVIar5/vnoG5KDKbe1hjz7mvtfN9qNqF5zRsjrNQEK/zlLtQES4QQQggf5ewYrERjvg2gPtipFm3B5WvlKCgu15z346p6QhRWP9PD7f26qTF4pHs9dH1zDQDvwU4NlwkRAeHEinot6kkIISR80ZPEYGItO7fkpOFsYQl+Oy090mro3F8Fo6mU6JCdjBW/5eFCUSnK7dpHYXla16vK5w93wtKdf+G5fjmC+nprmbm3Q20cOX8VPRqmOt/j5zm5dosRQgghSlE3lsFub5Hp8f1n+zbE+G7i60RV2X78Mg6pTCxuklk5DPzYRekRYAsf6iCrvMd63iS6rX12EnKHNENClEVRy4w1woTXBjdFr0bpzvfK7Pq2QhFCCAlv1LJjsKmDGqN9dhIKissx7bvfne/XT4vFMQXD0NVoen124pJy6W6wlFgblj/RBUUlFaidHCNYt2rhQx2Qf60cZXY77mhRQ9Z5+V13akZTac1RIoQQQvgo2DFYtDUCQ1rXxF/5xc5g5+62NRFhNglmClbLYuZEu6gaZMTJKiM51oqUWJvz6843JWPD4YvXX6corlOd5BgAgIlT1w2lJambEEIIcUXBjo/USIzClhd6oczuQFpc5WKVBSpzcfge63ET3ll1yO39v/XPQVK0VVYZ1Vz2i9GYFBxji8CuqbfCGqGul9REsyYTQgjREQU7PpTmsiJ370bpuCktFnVTYvC/38+qKpOJLP9QIzEKkRbvwUaXm1LcWl9evq0xDp8rwpgu2arqBACJMgMtTx7rWQ8/HzqP4e2yVJdBCCGEVKEEZT9KirHip8nd8fbwls73tr3UW1EZ6Qk3AqjGvHWpalaLEl1XqnuDGyOf/nlXC7ftWUnRWP1MD9zfsbaiuuglLS4Sq57ugfHd6vnl/IQQQkILBTsBIMYWgam3NcYzfRogJdaGOSNvTNLXtb50zszdbW+0fjgYQ+6QZnj8lpvQMisRADBreEvckpOGIa1q4PXBTTG8bRbeuLOp8xgGfRYGJYQQQgIVdWMFiLG8LqMBzao7X784sBH6zfrZ4zF9m6TDYjYhKykKJy8V49bG6RjRvpZgn8GtamBwK+EoKj1yhQghhJBgQcFOgPp2YmdculqGnIx40X0c1xtl/vvozdhw+IIgSJJLJOWHEEIICRnUjRWgmtdMRI+GaQCADtlJAIClj90s2MdxPdpJi4vEna1qwhYhb06bWN5MyMmx6hOJCSGEkGBALTtB4NOHOuDS1TKkx0di99Q+aDH9fwAAm4zRVp6YTRz2vtoHDgbZARIhhBASrKhlJwhYzCakXx+2nhBtwWuDmyI7JQZT+jdSXWZcpAUJURa9qkgIIYQELI6JTdQSRgoLC5GQkICCggLEx4vnyBBCCCEkcMh9flPLDiGEEEJCGgU7hBBCCAlpFOwQQgghJKRRsEMIIYSQkEbBDiGEEEJCGgU7hBBCCAlpFOwQQgghJKRRsEMIIYSQkBYywc7s2bNRp04dREZGokOHDtiyZYu/q0QIIYSQABASwc6SJUswefJkvPLKK9ixYwdatGiBvn374ty5c/6uGiGEEEL8LCSCnbfeegvjxo3DmDFj0LhxY8ybNw/R0dH46KOP/F01QgghhPhZ0Ac7ZWVl2L59O3r37u18z2QyoXfv3ti4caPHY0pLS1FYWCj4RwghhJDQFPTBzoULF2C325Geni54Pz09HXl5eR6Pyc3NRUJCgvNfVlaWL6pKCCGEED8I+mBHjSlTpqCgoMD57+TJk/6uEiGEEEIMEuHvCmiVkpICs9mMs2fPCt4/e/YsMjIyPB5js9lgs9mcXzPGAIC6swghhJAgUvXcrnqOiwn6YMdqtaJNmzZYtWoVBg8eDABwOBxYtWoVJk6cKKuMK1euAAB1ZxFCCCFB6MqVK0hISBDdHvTBDgBMnjwZo0aNQtu2bdG+fXvMmjULV69exZgxY2Qdn5mZiZMnTyIuLg4cx+lWr8LCQmRlZeHkyZOIj4/XrVwiRNfZd+ha+wZdZ9+g6+w7Rl1rxhiuXLmCzMxMyf1CItgZPnw4zp8/j6lTpyIvLw8tW7bEihUr3JKWxZhMJtSsWdOw+sXHx9Mvkg/QdfYduta+QdfZN+g6+44R11qqRadKSAQ7ADBx4kTZ3VaEEEIICR9hORqLEEIIIeGDgh0D2Ww2vPLKK4KRX0R/dJ19h661b9B19g26zr7j72vNMW/jtQghhBBCghi17BBCCCEkpFGwQwghhJCQRsEOIYQQQkIaBTuEEEIICWkU7Bho9uzZqFOnDiIjI9GhQwds2bLF31UKGrm5uWjXrh3i4uKQlpaGwYMH48CBA4J9SkpKMGHCBCQnJyM2NhZDhw51WyPtxIkTGDhwIKKjo5GWloZnn30WFRUVvvwoQWXGjBngOA5PPfWU8z26zvr566+/cN999yE5ORlRUVFo1qwZtm3b5tzOGMPUqVNRvXp1REVFoXfv3jh06JCgjEuXLmHkyJGIj49HYmIiHnzwQRQVFfn6owQsu92Ol19+GdnZ2YiKikK9evXw2muvCdZOouuszvr16zFo0CBkZmaC4zh8/fXXgu16Xdc9e/aga9euiIyMRFZWFt58803tlWfEEIsXL2ZWq5V99NFH7LfffmPjxo1jiYmJ7OzZs/6uWlDo27cvmz9/Ptu3bx/btWsXGzBgAKtVqxYrKipy7vPII4+wrKwstmrVKrZt2zbWsWNHdvPNNzu3V1RUsKZNm7LevXuznTt3su+//56lpKSwKVOm+OMjBbwtW7awOnXqsObNm7Mnn3zS+T5dZ31cunSJ1a5dm40ePZpt3ryZ/fnnn+zHH39khw8fdu4zY8YMlpCQwL7++mu2e/dudvvtt7Ps7GxWXFzs3Kdfv36sRYsWbNOmTeznn39mN910ExsxYoQ/PlJAeuONN1hycjJbtmwZO3r0KPviiy9YbGwse+edd5z70HVW5/vvv2cvvvgi++qrrxgAtnTpUsF2Pa5rQUEBS09PZyNHjmT79u1jn332GYuKimLvv/++prpTsGOQ9u3bswkTJji/ttvtLDMzk+Xm5vqxVsHr3LlzDABbt24dY4yx/Px8ZrFY2BdffOHcZ//+/QwA27hxI2Os8hfTZDKxvLw85z5z585l8fHxrLS01LcfIMBduXKF1a9fn61cuZJ1797dGezQddbP888/z7p06SK63eFwsIyMDDZz5kzne/n5+cxms7HPPvuMMcbY77//zgCwrVu3Ovf54YcfGMdx7K+//jKu8kFk4MCBbOzYsYL3hgwZwkaOHMkYo+usF9dgR6/rOmfOHFatWjXBveP5559nDRs21FRf6sYyQFlZGbZv347evXs73zOZTOjduzc2btzox5oFr4KCAgBAUlISAGD79u0oLy8XXOOcnBzUqlXLeY03btyIZs2aCdZI69u3LwoLC/Hbb7/5sPaBb8KECRg4cKDgegJ0nfX07bffom3btrjrrruQlpaGVq1a4f/+7/+c248ePYq8vDzBtU5ISECHDh0E1zoxMRFt27Z17tO7d2+YTCZs3rzZdx8mgN18881YtWoVDh48CADYvXs3fvnlF/Tv3x8AXWej6HVdN27ciG7dusFqtTr36du3Lw4cOIDLly+rrl/IrI0VSC5cuAC73e62EGl6ejr++OMPP9UqeDkcDjz11FPo3LkzmjZtCgDIy8uD1WpFYmKiYN/09HTk5eU59/H0PajaRiotXrwYO3bswNatW9220XXWz59//om5c+di8uTJeOGFF7B161Y88cQTsFqtGDVqlPNaebqW/GudlpYm2B4REYGkpCS61tf97W9/Q2FhIXJycmA2m2G32/HGG29g5MiRAEDX2SB6Xde8vDxkZ2e7lVG1rVq1aqrqR8EOCXgTJkzAvn378Msvv/i7KiHn5MmTePLJJ7Fy5UpERkb6uzohzeFwoG3btvj73/8OAGjVqhX27duHefPmYdSoUX6uXej4/PPPsXDhQixatAhNmjTBrl278NRTTyEzM5OucxijbiwDpKSkwGw2u41YOXv2LDIyMvxUq+A0ceJELFu2DGvWrEHNmjWd72dkZKCsrAz5+fmC/fnXOCMjw+P3oGobqeymOnfuHFq3bo2IiAhERERg3bp1ePfddxEREYH09HS6zjqpXr06GjduLHivUaNGOHHiBIAb10rqvpGRkYFz584JtldUVODSpUt0ra979tln8be//Q333HMPmjVrhvvvvx+TJk1Cbm4uALrORtHruhp1P6FgxwBWqxVt2rTBqlWrnO85HA6sWrUKnTp18mPNggdjDBMnTsTSpUuxevVqt2bNNm3awGKxCK7xgQMHcOLECec17tSpE/bu3Sv45Vq5ciXi4+PdHjrhqlevXti7dy927drl/Ne2bVuMHDnS+Zqusz46d+7sNn3CwYMHUbt2bQBAdnY2MjIyBNe6sLAQmzdvFlzr/Px8bN++3bnP6tWr4XA40KFDBx98isB37do1mEzCR5vZbIbD4QBA19koel3XTp06Yf369SgvL3fus3LlSjRs2FB1FxYAGnpulMWLFzObzcYWLFjAfv/9dzZ+/HiWmJgoGLFCxD366KMsISGBrV27lp05c8b579q1a859HnnkEVarVi22evVqtm3bNtapUyfWqVMn5/aqIdF9+vRhu3btYitWrGCpqak0JNoL/mgsxug662XLli0sIiKCvfHGG+zQoUNs4cKFLDo6mn366afOfWbMmMESExPZN998w/bs2cPuuOMOj0N3W7VqxTZv3sx++eUXVr9+/bAfEs03atQoVqNGDefQ86+++oqlpKSw5557zrkPXWd1rly5wnbu3Ml27tzJALC33nqL7dy5kx0/fpwxps91zc/PZ+np6ez+++9n+/btY4sXL2bR0dE09DyQ/fvf/2a1atViVquVtW/fnm3atMnfVQoaADz+mz9/vnOf4uJi9thjj7Fq1aqx6Ohoduedd7IzZ84Iyjl27Bjr378/i4qKYikpKezpp59m5eXlPv40wcU12KHrrJ/vvvuONW3alNlsNpaTk8M++OADwXaHw8Fefvlllp6ezmw2G+vVqxc7cOCAYJ+LFy+yESNGsNjYWBYfH8/GjBnDrly54suPEdAKCwvZk08+yWrVqsUiIyNZ3bp12YsvvigYykzXWZ01a9Z4vC+PGjWKMabfdd29ezfr0qULs9lsrEaNGmzGjBma684xxptWkhBCCCEkxFDODiGEEEJCGgU7hBBCCAlpFOwQQgghJKRRsEMIIYSQkEbBDiGEEEJCGgU7hBBCCAlpFOwQQgghJKRRsEMICVoLFixwW5Fdb3Xq1MGsWbMMPQchxFgU7BBCgtbw4cNx8OBBf1eDEBLgIvxdAUIIUSsqKgpRUVH+rgYhJMBRyw4hxG8cDgdyc3ORnZ2NqKgotGjRAl9++SUAYO3ateA4DsuXL0fz5s0RGRmJjh07Yt++fc7jXbuxdu/ejZ49eyIuLg7x8fFo06YNtm3b5tz+3//+F02aNIHNZkOdOnXwr3/9S1Cfc+fOYdCgQYiKikJ2djYWLlzoVuf8/Hw89NBDSE1NRXx8PG655Rbs3r1b5ytDCNETtewQQvwmNzcXn376KebNm4f69etj/fr1uO+++5Camurc59lnn8U777yDjIwMvPDCCxg0aBAOHjwIi8XiVt7IkSPRqlUrzJ07F2azGbt27XLut337dtx999149dVXMXz4cPz666947LHHkJycjNGjRwMARo8ejdOnT2PNmjWwWCx44okncO7cOcE57rrrLkRFReGHH35AQkIC3n//ffTq1QsHDx5EUlKScReLEKKe5qVECSFEhZKSEhYdHc1+/fVXwfsPPvggGzFihHOF5cWLFzu3Xbx4kUVFRbElS5YwxhibP38+S0hIcG6Pi4tjCxYs8Hi+e++9l916662C95599lnWuHFjxhhjBw4cYADYli1bnNv379/PALC3336bMcbYzz//zOLj41lJSYmgnHr16rH3339f2QUghPgMtewQQvzi8OHDuHbtGm699VbB+2VlZWjVqpXz606dOjlfJyUloWHDhti/f7/HMidPnoyHHnoI//nPf9C7d2/cddddqFevHgBg//79uOOOOwT7d+7cGbNmzYLdbsf+/fsRERGBNm3aOLfn5OS4dZMVFRUhOTlZUE5xcTGOHDmi7AIQQnyGgh1CiF8UFRUBAJYvX44aNWoIttlsNlXBw6uvvop7770Xy5cvxw8//IBXXnkFixcvxp133qlbnatXr461a9e6bTN6CDwhRD0KdgghftG4cWPYbDacOHEC3bt3d9teFexs2rQJtWrVAgBcvnwZBw8eRKNGjUTLbdCgARo0aIBJkyZhxIgRmD9/Pu688040atQIGzZsEOy7YcMGNGjQAGazGTk5OaioqMD27dvRrl07AMCBAweQn5/v3L9169bIy8tDREQE6tSpo/EKEEJ8hYIdQohfxMXF4ZlnnsGkSZPgcDjQpUsXFBQUYMOGDYiPj0ft2rUBANOnT0dycjLS09Px4osvIiUlBYMHD3Yrr7i4GM8++yyGDRuG7OxsnDp1Clu3bsXQoUMBAE8//TTatWuH1157DcOHD8fGjRvx3nvvYc6cOQCAhg0bol+/fnj44Ycxd+5cRERE4KmnnhIMbe/duzc6deqEwYMH480330SDBg1w+vRpLF++HHfeeSfatm1r/IUjhCjn76QhQkj4cjgcbNasWaxhw4bMYrGw1NRU1rdvX7Zu3TpngvJ3333HmjRpwqxWK2vfvj3bvXu383h+gnJpaSm75557WFZWFrNarSwzM5NNnDiRFRcXO/f/8ssvWePGjZnFYmG1atViM2fOFNTnzJkzbODAgcxms7FatWqxTz75hNWuXduZoMwYY4WFhezxxx9nmZmZzGKxsKysLDZy5Eh24sQJQ68VIUQ9jjHG/B1wEUKIq7Vr16Jnz564fPky5cMQQjShSQUJIYQQEtIo2CGEEEJISKNuLEIIIYSENGrZIYQQQkhIo2CHEEIIISGNgh1CCCGEhDQKdgghhBAS0ijYIYQQQkhIo2CHEEIIISGNgh1CCCGEhDQKdgghhBAS0ijYIYQQQkhI+//Z2Vp5dzO4ngAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "episodes_list = list(range(len(return_list)))\n",
    "plt.plot(episodes_list, return_list)\n",
    "plt.xlabel('episode')\n",
    "plt.ylabel('return')\n",
    "plt.title(f'ActorCritic on {env_name}')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:16:37.200109Z",
     "end_time": "2023-07-06T10:16:37.543736Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mv_return = rl_utils.moving_average(return_list, window_size=9)\n",
    "plt.plot(episodes_list, mv_return)\n",
    "plt.xlabel('episode')\n",
    "plt.ylabel('return')\n",
    "plt.title(f'ActorCritic on {env_name}')\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:16:37.542739Z",
     "end_time": "2023-07-06T10:16:37.850009Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "start_time": "2023-07-06T10:16:37.850009Z",
     "end_time": "2023-07-06T10:16:37.912272Z"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
